Motivation
The motivation behind exploring "Applying Blockchain (Distributed Ledger Technology) for Product Origin Traceability" stems from the need to tackle practical challenges faced by Vietnamese enterprises in tracking product origins within their value chains This study aims to enhance the transparency and traceability of food brands, leveraging blockchain technology, which has emerged as a revolutionary force in the IT sector, facilitating the shift from centralized to decentralized systems Product origin traceability, a crucial aspect since the emergence of mad cow disease in 1986, has evolved significantly, integrating advanced technologies like RFID, IoT, and blockchain This process allows for the tracking and identification of products throughout the entire value chain, from raw materials to distribution, ensuring that product information is consistently stored and accessible The primary goal of implementing blockchain for traceability is to protect consumers by enabling swift and accurate identification of products through an immutable data pipeline, ultimately benefiting regulators, manufacturers, and consumers by enhancing trust in food quality, improving operational efficiency, and safeguarding brand reputation against counterfeiting.
Figure 1 - General architecture of the product origin traceability using a Blockchain platform
The current landscape of global blockchain service providers focusing on product traceability is limited and costly, making it impractical for the Vietnamese market To better align with the infrastructure and budget of local enterprises, this article proposes a lean and cost-effective blockchain-based traceability solution This system will enable partners to engage in transaction verification and information sharing while ensuring the integrity and origin of products are easily verifiable By efficiently tracking data changes within the blockchain, the solution aims to reduce time and costs associated with verifying product origins Ultimately, this approach will help combat the prevalence of counterfeit products in Vietnam, thereby protecting the reputation of high-quality Vietnamese brands.
Problem statement
The demand for Vietnamese agricultural exports has surged post-COVID-19, necessitating robust quality assurance and provenance through product origin traceability This traceability not only enhances product quality for the domestic market but also boosts access to global sales channels, allowing businesses to command higher prices and increase profits Implementing blockchain technology in traceability enhances reliability, fosters trust among consumers and stakeholders, and facilitates penetration into premium market segments Amid rising counterfeit issues in the local market, effective origin traceability is crucial for ensuring food safety and hygiene Small and medium-sized enterprises are optimistic about leveraging advanced technologies to create closed value chains, which is essential for maintaining consumer trust Established brands like Vissan, Masan, and Ba Huan are encouraged to adopt these solutions to tackle traceability challenges, eliminate reliance on central authorities, and address issues such as data inconsistencies, inefficient manual processes, contamination risks, audit difficulties, and quality control.
This thesis explores open-source Blockchain (DLT) platforms and proposes an optimal solution for enhancing trust and immutability in multi-actor processes related to product origin traceability By conducting an empirical comparison of popular DLTs, the research aims to address the challenges faced in establishing consensus among organizations within the value chain The DLT facilitates secure transactions between parties, fostering trust and ensuring that recorded transactions remain immutable within the blockchain network.
”Blockchain” and “Distributed Ledger Technology (DLT)”, in this study, both terms are treated synonymously and throughout the thesis content, Blockchain (DLT) is used.
Overview of blockchain adoption
Blockchain technology is revolutionizing various industries by providing a decentralized, tamper-evident ledger that serves as a verifiable single source of truth This immutable record enhances traditional bookkeeping, reducing human errors and ensuring data integrity In retail, blockchain improves product traceability and transparency, minimizing losses from shipping to shelf and maintaining accurate records for recalls In banking and financial services, consortiums can facilitate cross-border asset transfers without centralized control Manufacturing and distribution benefit from blockchain by enhancing data security and transparency through provenance tracking, which documents the origin and ownership of goods throughout the supply chain Additionally, the automotive industry leverages shared blockchain systems to enable real-time, secure data sharing among suppliers, transporters, and retailers, enhancing coordination and tracking of automotive parts.
Blockchain technology, specifically as a private permissioned platform, has emerged as a vital tool for enhancing product origin traceability within value chains, enabling improved traceability and transparency High-value goods benefit from storing information in a tamper-proof, distributed ledger, which ensures accurate tracking Major organizations, including Google, Facebook, Amazon, Microsoft, Oracle, and IBM, have developed blockchain applications to maintain precise data histories Since the rise of Bitcoin in 2016, numerous companies have invested in blockchain projects across various industries IBM FoodTrust exemplifies this trend by using blockchain to create a secure ecosystem for food supply management, fostering trust and transparency among transaction partners Nestlé, a founding member of IBM FoodTrust since 2017, has expanded its blockchain initiatives to enhance transparency and sustainability for consumers Additionally, IBM has collaborated with Walmart to ensure the traceability of Chinese pork, further demonstrating the practical applications of blockchain in supply chain management.
Mexican mangoes benefit from IBM FoodTrust's collaboration with major global agri-food companies like Unilever and Dole, utilizing blockchain technology to enhance product tracking and information sharing throughout the processing chain This technology allows for comprehensive monitoring of various factors, including origin, breeding, production processes, and storage conditions By establishing their own blockchain networks, these companies aim to address the complexities of cross-country operations and improve origin traceability, creating a unified source of truth for all stakeholders Additionally, prominent software development agencies such as Consensys, Accenture, Deloitte, and SettleMint offer blockchain platform solutions, fostering collaboration among multiple parties in diverse product value chains.
Vissan business model
Founded in November 1970, Vissan has emerged as a leading enterprise in Vietnam's food industry, specializing in animal husbandry and the production and trading of fresh and processed foods With a robust nationwide distribution network and exports to various countries, Vissan is committed to delivering safe, high-quality products that offer significant nutritional value to the community The company continuously invests in its growth to maintain its position as the largest food producer, processor, and distributor in the country, while also expanding its reach internationally Over the decades, Vissan has earned recognition as one of Vietnam's top food manufacturers, excelling in the processing and trading of fresh meat, processed foods, and related products.
In 2021, Vissan aims to achieve a revenue target of VND 5,100 billion, maintaining the same level as in 2020 The company plans to produce 18,552 tons of fresh food, including pork and beef, which is consistent with its output from the previous year, while also projecting an 8% increase in processed food production.
Vissan aims to produce 30,350 tons of products while anticipating a 6% rise in operating expenses, totaling VND 841,460 billion To enhance manufacturing efficiency and revenue, the company is investing in advanced factory technologies and food processing equipment Supported by the Vietnamese government's initiatives to attract investment in agriculture, Vissan is modernizing its facilities and adopting new end-to-end production technologies Implementing a traceability system for its pork products will not only enhance consumer trust in quality and origin but also increase domestic sales and support global export ambitions in the coming years.
The article outlines the comprehensive journey from manufacturing to distribution and sales, highlighting typical data integration at each stage However, the actual process is characterized by numerous silos, making it complex due to the involvement of various vendors, systems, and organizations within Vissan's value chain Consequently, fully implementing this intricate flow within the constraints of this thesis is not feasible.
Figure 3 - General full process from Manufacturing phase to Selling phase (Vissan)
Thesis scope
Below are the main objectives within this study (any other items not mentioned in this scope are considered out-of-scope ones: (1) To study the general permissioned
This article explores the execution of smart contracts on blockchain (DLT) platforms, focusing on consensus algorithms and comparing various open-source options before selecting Hyperledger Fabric for a demo on product origin traceability It examines Hyperledger Fabric's architecture and technical design, assessing its performance and applications in business contexts Additionally, the article details a demonstration of a typical value chain process for the Vissan Company, tracking products from manufacturing to retail using Hyperledger Fabric DLT.
Figure 4 - The demo process flow with the smart contract to save product status to the ledger
Figure 5 - The demo process flow with smart contract
The demo showcases a novel process flow for Vissan food product traceability, tracking the journey from production to the customer while updating product statuses on the Hyperledger Fabric ledger through smart contracts, ensuring immutable and transparent data This thesis focuses on implementing a minimum viable product that allows querying of product statuses from the ledger, demonstrating the integration of business logic through smart contracts across Fabric nodes in a distributed environment The demo meets three essential requirements: (R1) providing a permissioned blockchain solution for managing stakeholders in the Vissan value chain; (R2) enabling traceability of product origins at each stage of the value chain; and (R3) ensuring data security and immutability, allowing users to view transaction details in a public explorer for real-time status updates.
- not populate all detailed Vissan product data at each step (only to indicate the product ID and all statuses at each step are populated to the DLT)
- not consider the revocation of the product created (as the meat product expiration is short, up to 3-4 days)
The mobile and website frontends do not offer QR scanning capabilities for product information queries; instead, they solely display product information or status updates, which are managed internally by users in the DLT system.
Vissan's offline operations lack essential features for effective daily business management, including user management, product management, and store management, as well as any other items not specified within the defined scope.
Thesis organization
The thesis will consist of five parts as listed below:
Chapter 1 outlines the motivation behind the research topic and defines the thesis's scope It introduces key issues related to product origin traceability and presents Vissan company as the chosen case study for demonstrating the proposed system solutions.
Chapter 2 provides a comprehensive overview of essential concepts related to Blockchain technology, including Distributed Ledger Technology (DLT), hash functions, Merkle trees, ECDSA, and consensus mechanisms, alongside smart contracts It reviews scholarly works that explore the application of Blockchain for product traceability and offers a comparative analysis of various open-source permissioned Blockchain platforms.
Chapter 3 presents the proposed approach utilizing the final Distributed Ledger Technology (DLT) selected after a comparative study of Hyperledger Fabric It details the architectural design and key technical components, including the network, organizations, ordering service, smart contract, ledger, and transaction flow Additionally, the chapter showcases a demo implementation for tracing the origin of Vissan products, demonstrating the innovative process flow and the design of a minimum viable product solution.
Chapter 4 examines the performance metrics and benchmarking experiments of Hyperledger Fabric, focusing on key indicators such as transactions per second (TPS), network throughput, and CPU usage percentage It also highlights the extensive adoption of Hyperledger Fabric across various business sectors.
Chapter 5: provides the blockchain enablement and security analysis of the proposed solution and the conclusion, further recommendation of the study
Existing solutions for food origin tracing
There are existing solutions for food origin traceability using Blockchain (DLT) in the Vietnam local market as well as global regions, to list a few:
Table 1 - Existing products (companies) in food origin traceability
Product / Company Description Market te-food.com Farm-to-table fresh food traceability Vietnam,
Global traceverified.com Electronic traceability for food quality assurance from farm to table
Vietnam is leveraging innovative technologies like QR codes and barcodes through platforms such as traceproduct.com and icheck.com.vn to enhance the traceability of agri-food products This initiative aims to transform the agriculture industry, ensuring greater transparency and accountability Additionally, settlemint.com is utilizing distributed ledger technologies to improve supply chain management, further supporting the modernization of agricultural practices in Vietnam.
IBM FoodTrust Blockchain enhances the global food supply chain by fostering consumer trust and improving food quality across the industry It offers real-time traceability and valuable consumer insights, contributing to a more transparent food ecosystem.
SAP fkon.de Food supply chain Global kaiosid.com Traceability solution for consumer goods Global
Recent research has explored the integration of blockchain technology with smart contracts, IoT, and NFC protocols to enhance the automation of multi-actor processes in food traceability While existing literature emphasizes the benefits of blockchain for organizations, there is a lack of analysis on its adoption at both individual and organizational levels Challenges in product traceability, such as lengthy transaction times and stakeholder disengagement, can be addressed by fostering stronger connections among producers, consumers, and markets, ultimately leading to increased income The implementation of Distributed Ledger Technology (DLT) in product traceability can significantly improve food safety, quality, and sustainability by reducing risks and enhancing efficiency through transparency Additionally, smart contracts facilitate automation within the value chain, enabling real-time management of transactions and product attributes This capability allows for comprehensive tracking of products from farm to table, revolutionizing the food retail industry and enhancing consumer trust The following studies illustrate the application of blockchain in ensuring origin traceability for food and agricultural products.
Table 2 - Studies of using blockchain for food traceability
A blockchain use case in food distribution: Do you know where your food has been?
Cen et al [46] Improving Business Process Interoperability by Shared Ledgers
Edwards et al [47] When blockchain meets the supply chain: A Systematic Literature Review on Current Development and Potential Applications
Alzahrani et al [48] Block-Supply Chain: A New Anti-Counterfeiting Supply Chain Using
Feng Tian [49] An agri-food supply chain traceability system for China based on RFID & blockchain technology
Feng Tian [50] A Supply Chain Traceability System for Food Safety Based on HACCP,
Ramundo et al [51] State of the art of technology in the food sector value chain towards the
IoT Daniel et al [52] Blockchain application in food supply information security
Baralla et al [53] Ensure Traceability in European Food Supply Chain by Using a
Chen et al conducted a thematic analysis on the processes, benefits, and challenges of adopting blockchain technologies in food supply chains Similarly, Oslen et al explored the applications, limitations, costs, and benefits of blockchain technology within the food industry Together, these studies highlight the transformative potential of blockchain in enhancing transparency and efficiency in food supply chains while addressing the associated challenges and costs.
Blockchain Meets Genomics: Governance Considerations for Promoting Food Safety and Public Health
Mondal et al [57] Blockchain Inspired RFID-Based Information Architecture for Food
Xu et al [58] Application of blockchain technology in food safety control: current trends and prospects
Feng et al [59] Applying blockchain technology to improve agri-food traceability: a review of development methods, benefits, and challenges
Qian et al [60] Filling the trust gap of food safety in food trade between the EU and China:
An interconnected conceptual traceability framework based on blockchain
Hao et al [61] A Novel Visual Analysis Method of Food Safety Risk Traceability Based on Blockchain
Adnan et al [62] Application of Blockchain and Internet of Things to Ensure Tamper-Proof
Data Availability for Food Safety
Behnke et al [63] Boundary conditions for traceability in food supply chains using blockchain technology
Parshar et al [64] Blockchain-Based Traceability and Visibility for Agricultural Products: A
Decentralized Way of Ensuring Food Safety in India
Adnan et al [65] Blockchain-Based Traceability System That Ensures Food Safety
Measures to Protect Consumer Safety and COVID-19 Free Supply Chains
Fundamental knowledge of Blockchain (DLT)
Satoshi Nakamoto introduced Bitcoin as a decentralized peer-to-peer electronic cash system that eliminates the need for trust through the use of digital signatures and Merkle trees By timestamping transactions and hashing them into a continuous chain of proof-of-work, Bitcoin creates an immutable record that cannot be altered without redoing the computational effort This process not only establishes the longest chain as evidence of transaction history but also relies on the collective CPU power from participants solving complex mathematical problems defined by Bitcoin's technical framework.
Figure 6 - Digital Signatures (Bitcoin whitepaper, 2009) Figure 7 - Hashed-chain of blocks (Bitcoin whitepaper, 2009)
Blockchain technology, as described by NIST authors, is an immutable digital ledger system operating in a decentralized manner without a central authority It allows users to record transactions in a public ledger, ensuring that once published, transactions cannot be altered This technology underpins modern cryptocurrencies, utilizing cryptographic functions for secure transactions through public and private keys Users may earn cryptocurrency by solving cryptographic puzzles, contributing to an expanding list of time-stamped, irrevocable blocks of records shared across a peer-to-peer network Each block references previous data, and transactions are validated through consensus among participants While distributed ledgers face design limitations, the Proof of Work (PoW) approach has evolved significantly since 2009, leading to the development of new consensus algorithms that enhance blockchain’s role in the cryptocurrency domain The popularity of blockchain technology has surged, giving rise to various public permissionless blockchains in the global market, inspired by the principles outlined in the Bitcoin white paper.
- Ethereum [8] designs the proof-of-stake calculating the weight of a node as being proportional to its currency holdings and not the computational resources
Polkadot introduces a sophisticated consensus mechanism that utilizes nominated proof-of-stake for validator selection, alongside a combination of GRANDPA (GHOST-based Recursive Ancestor Deriving Prefix Agreement) for blockchain state finalization and BABE (Blind Assignment for Blockchain Extension) for block production.
- Solana [10] implements the proof-of-history which is proof for verifying order and passage of time between events
Binance Smart Chain employs Proof of Authority (PoA) for staking and governance, facilitating the integration of blockchain technology across various industries beyond just asset management in the financial sector.
Blockchain is defined as a distributed, write-only ledger that securely records transactions, providing transparency, efficiency, and security While often associated with cryptocurrencies, its broader applications extend to permissioned Blockchain (DLT) for product origin traceability This application enhances trust among multiple stakeholders in an enterprise's value chain, focusing on improving processes rather than the rapidly evolving cryptocurrency use cases in financial services.
2.2.1 Hash function and Merkel tree
Hash functions and Merkle trees play a crucial role in various security and cryptography applications, serving as fundamental components in blockchain development A hash function must meet specific properties to ensure its effectiveness and reliability.
- Pre-image resistance, given the hash value h, it is very difficult (unlikely) or impossible to find a value m such that
- Second pre-image resistance, given a value , it must be very difficult or impossible to find a value such that
- Collision free, it must be very difficult or impossible (unlikely) to find a value such that
Currently, the security hash functions defined and recommended by NIST are SHA-256, there is no collisions have been found to date for the SHA-256 In SHA-
256, messages up to 2 bit (2.3 exabytes, or 2.3 billion gigabytes) are transformed into digests of size 256 bits (32 bytes)
Figure 8 - Merkle tree and chain of blocks (Bitcoin whitepaper, 2009)
Merkle trees, introduced by R Merkle, are essential for securely and efficiently validating large data structures and verifying transactions This binary tree structure is created by computing and combining the hashes of an entire dataset, with the leaf nodes representing the data hashes Intermediate nodes contain hashes generated from concatenating the hashes of their child nodes, culminating in a final hash known as the root node's hash value The Merkle root serves as a compact representation of the entire dataset's integrity, allowing for quick verification; any alteration in the tree's hashes results in a change to the Merkle root, signaling potential data integrity issues.
2.2.2 Elliptic Curve Digital Signature Algorithm (ECDSA)
The Elliptic Curve Digital Signature Algorithm (ECDSA), proposed by Scott Vanstone in 1992, is the first elliptic curve signature algorithm that effectively satisfies the required equations ECDSA operates by taking a message hash and performing elliptic curve arithmetic with the message, a private key, and a random number to create a signature This signature can then be verified by anyone possessing the public key, the original message, and the signature itself through simple elliptic curve calculations In the context of Bitcoin, ECDSA is utilized with the secp256k1 elliptic curve The process of signing and verifying messages between users A and B using ECDSA involves user A establishing the elliptic curve parameters and generating the corresponding key pair.
User A possesses a private key and a corresponding public key, which can be derived from the private key using the parameter point G in the ECDSA elliptic curve.
(a) user A generates a random number k based on the ECDSA algorithm, uses points G to calculate the public key
(b) user A calculates the hash value of the message M:
(c) user A calculates the eigenvalues of an elliptic curve , of which
, ( is the multiplicative inverse of the modulus of k)
(d) is the digital signature of user A User A sends the elliptic curve parameters and User A’s public key to User B for verification of the correctness of the signature
(a) user B calculates the hash value of the message M:
(c) calculation , if then the signature is validated
The security of elliptic curve cryptography relies on the difficulty of the elliptic curve discrete logarithm problem, which is significantly more complex than the traditional discrete logarithm problem This complexity provides elliptic curve cryptosystems with enhanced cryptographic strength, resulting in smaller computational parameters, shorter keys, faster operations, and more compact signatures Consequently, elliptic curve ciphers are especially advantageous for various applications, particularly in the realm of blockchain technology.
The next part discusses further outstanding features of blockchain technology regarding immutability, security, speed, smart contract, and consensus as an important part of distributed ledger technology
Blockchain's standout feature is its immutability, ensuring that the distributed ledger cannot be altered, deleted, or reversed without the consensus of over 51% of nodes While gaining control of more than half of the nodes is highly unlikely, it remains theoretically possible with significant resources Immutability pertains to both the data and code within the blockchain; data records are considered untraceable once entered, yet they can be erroneous before integration Although consensus mechanisms aim to verify data input, they are limited by the honesty of participants Additionally, the code's immutability is questioned, as no code can perfectly meet all operational requirements, leading to frequent adjustments in the blockchain code.
The distributed ledger technology is renowned for its robust security features, utilizing cryptographic encryption to secure transactions among participating organizations The integration of public and private keys enhances both integrity and authentication, effectively preventing manipulation Central to blockchain security are cryptographic hash functions, which produce unique identifiers of fixed lengths, regardless of the input Each hash serves as an identifier for a block and is linked to the hash of the preceding block, while hash functions play a crucial role in consensus mechanisms to validate ongoing transactions.
The distributed ledger technology has effectively addressed the transaction delays commonly found in traditional banking systems The speed of blockchain transactions is influenced by various factors including the consensus algorithm, block size, transaction fees, network conditions, and hardware configuration Overall, blockchain enhances global transactions by minimizing block times, which is the duration needed to create a new block Additionally, increasing the block size leads to reduced transmission times, thereby boosting transaction speeds.
Smart contracts, a term first introduced by Nick Szabo in the early 1990s, refer to "a set of promises, specified in digital form, including protocols within which the parties perform on these promises." Today, they are crucial in blockchain technology, functioning as decentralized programs that foster cooperation and trust among various business entities through advanced business logic By ensuring immutable data that can only be added to and not altered or deleted, smart contracts enhance historical traceability and make malicious activities costly and permanently recorded on the blockchain.
Figure 10 - Smart contract execution (Hyperledger Foundation, 2020)
Smart contracts operate on a blockchain platform, ensuring that storage, reading, and execution processes are transparent, traceable, and immutable Additionally, the consensus algorithms integrated into the blockchain create a state machine system that enhances the efficiency of smart contract operations.
Consensus algorithms
Consensus mechanisms are crucial for ensuring fault tolerance in blockchain transaction verification, maintaining unity among an expanding network of nodes As the number of participants grows, achieving agreement becomes increasingly challenging, particularly in public blockchains where transaction validation is essential To uphold the authenticity of transactions, a secure consensus agreement among participants is necessary Various consensus mechanisms have been developed, each with unique principles and applications, aimed at facilitating regular secure updates to the distributed ledger A key technique involved is state machine replication, which ensures that shared states adhere to predefined transition rules This interaction among replicas is vital for reaching consensus on state modifications, ultimately determining the finality of each state and ensuring identical outputs across the network.
Implementing consensus in distributed systems is complex, requiring mechanisms that ensure fault tolerance, resilience to failures, and network partitioning while maintaining delay persistence Security measures are essential to manage malicious nodes through synchronization and message broadcasting In distributed ledgers like blockchain, consensus preserves critical properties that enhance network efficiency, including safety, viability, and fault tolerance Consensus protocols are evaluated based on their ability to ensure all nodes produce consistent and valid outputs, while liveness refers to the mechanism's capability to facilitate node contributions effectively Additionally, the consensus mechanism must recover from node failures to uphold fault tolerance Research by Lashkar and Musilek provides a comparative analysis of consensus mechanisms, highlighting traditional approaches like Paxos, which improves fault tolerance amid unreliable systems One prevalent issue in distributed ledgers is Byzantine errors, where compromised nodes provide misleading responses, as first identified by Lamport.
Recent studies on blockchain consensus mechanisms highlight the development of alternative protocols aimed at addressing the limitations of existing approaches, applicable across various domains, particularly in decentralized applications (DApps), IoT, and cloud computing The integration of consensus algorithms is notably prevalent in cryptocurrencies, supply chain platforms, and healthcare systems, reflecting a diverse distribution of mechanisms tailored for specific applications within distributed ledgers As distributed ledger technology evolves, the demand for robust consensus protocols has surged, leading to the creation of new mechanisms that transition from permissionless to permissioned blockchains, enhancing transaction verification security The effectiveness of traditional consensus protocols, like Proof of Work (PoW), is often inadequate for environments with stringent financial regulations, prompting organizations to adopt flexible consensus mechanisms based on their specific needs The Hyperledger Foundation has significantly contributed to this landscape by offering various DLT solutions, promoting the use of open-source distributed ledger technologies across multiple industries An empirical analysis by Lashkar and Musilek categorized over 130 consensus algorithms into eight distinct groups based on characteristics such as scalability, finality, and centralization, providing insights into their functionalities and trade-offs.
Figure 12 - Consensus classification (Lashkari and Musilek [15], 2016)
This comparative view [15] also provided the applicability of each category among the distribution in different blockchain application domains
Table 3 - Consensus in popular Cryptocurrencies ([15])
5 IOST Proof of Believability Permissioned Probabilistic
Tables 3 and 4 provide an overview of key consensus mechanisms utilized in popular cryptocurrencies and blockchain (DLT) platforms Due to the focused nature of this thesis, additional consensus methods not included in these tables are not addressed.
Table 4 - Consensus in popular Blockchain (DLT) platforms ([15][66])
# Blockchain (DLT) Consensus Accessibility Finality
1 Ethereum PoW / PoS (version 2) Permissionless Probabilistic
2 Hyperledger Fabric PBFT/CFT/Raft Permissioned Deterministic
3 Hyperledger Sawtooth PoET Both Probabilistic
6 Quorum Raft/IBFT Permissioned Probabilistic
11 Corda R3 Notary Pool Permissioned Deterministic
12 Credits DPoS + BFT Permissionless Probabilistic
13 Elements Strong Federations Permissioned Deterministic
14 IBM Blockchain PoET Permissioned Probabilistic
16 NEM Proof of Importance Permissioned/
Figure 13 illustrates the typical transaction flow and latency associated with blockchain platforms that utilize random leader election consensus mechanisms, such as Proof of Work (PoW) and Proof of Elapsed Time (PoET) Unlike Practical Byzantine Fault Tolerance (PBFT), this consensus model lacks discrete rounds The diagram outlines key operational phases: (a) Request, where a client submits a transaction; (b) Commit, where a validator publishes the transaction in a block; (c) Fork, where competing blocks may be published by validators; (d) Resolve, where validators address the fork upon receiving the winning block; and (e) Consistency, ensuring that subsequent reads from any validator yield consistent results Various consensus types, differing in algorithm design principles—ranging from vote-based to capability-based, and encompassing both permissioned and permissionless environments—are summarized in Tables 3 and 4, along with their definitions.
Figure 13 - Transaction flow in PoW consensus (Hyperledger Foundation, 2020)
Paxos, the pioneering consensus algorithm, enables the selection of a unique value amidst network failures It categorizes nodes into three roles: proposers, acceptors, and learners Proposers send messages with a proposal number to acceptors, who evaluate the proposals based on their timeline, accepting only those that are newer than their current known values Acceptors then respond with the outcome of the proposal, including whether it was accepted or rejected, along with the proposal number and accepted values Proposers must verify if a majority of acceptors have rejected their proposal; if so, they update their proposal number accordingly If accepted, the value is broadcasted to all learners in the network For consensus to be achieved in Paxos, a proposer must secure a majority of acceptances from the acceptors.
Raft is a consensus algorithm originally modified by Quorum, serving as a simplified extension of the theoretical Paxos algorithm It features a state replication model that ensures all transactions are shared among participating nodes, enabling a leader node to create the next block while avoiding the generation of empty blocks To maintain functionality in a blockchain network with failing nodes, Raft mandates the deployment of at least one operational node Additionally, Raft is supported as the recommended consensus mechanism in Hyperledger Fabric.
BFT-Raft is an advanced alternative to the traditional Raft protocol, combining the security and fault tolerance features of both Byzantine Fault Tolerance (BFT) and Raft It utilizes digital signatures to ensure message authenticity and integrity, effectively preventing tampering Messages with invalid signatures can be promptly identified and discarded, as they are signed by both nodes and users Additionally, BFT-Raft employs a voting process to elect leader nodes, ensuring network functionality even in the presence of Byzantine faults, provided there are at least 3f + 1 nodes in the network.
The Proof of Work (PoW) mechanism begins by computing the hash of the block header, which includes a nonce that miners frequently modify to generate various hashes To achieve consensus, the earned value must stay within a specific range PoW establishes a complex puzzle that requires collaboration among nodes to maintain a network-wide agreement on the transmission of new blocks Miners who successfully solve the puzzle are permitted to add a new block to the blockchain The puzzle's difficulty is adjusted, and it involves estimating the nonce value, which is combined with the block header information to produce the SHA hash.
A 256 hash function transforms all inputs into a unique hash value When the output hash falls below a predetermined threshold, the miner's estimated nonce is accepted, enabling them to add a new block to the blockchain Once the target value is achieved, the miner broadcasts the block across the network, prompting every node to verify the hash's authenticity and integrate the corresponding blocks into their own blockchain.
Proof of Stake (PoS), initially introduced for Peercoin, serves as a more energy-efficient alternative to Proof of Work (PoW) by reducing the excessive power consumption associated with node operations However, the approach of selecting block proposers based on account balances has raised fairness concerns, leading to various proposals that integrate stake sizing Despite its advantages in energy efficiency, PoS remains vulnerable to certain attacks As a result, several blockchain projects have shifted from PoW to PoS over time to balance energy consumption and security.
2.4.6 Delegated Proof of Stake (DPoS) [99] [100] [101] [102]
Delegated Proof of Stake (DPoS) is an advanced consensus mechanism that surpasses traditional methods like Proof of Work (PoW) and Proof of Stake (PoS) by enabling faster block generation and transaction processing This system reduces energy consumption through a one vote per share approach, which increases the number of preprocessors involved In DPoS, stakeholders vote for randomly selected witnesses to maintain consensus, incentivizing them based on their block generation and penalizing them for underperformance However, DPoS faces challenges related to decentralization, as it relies on a limited number of validators, making it susceptible to significant attacks such as 51% attacks, ranged attacks, and balanced attacks Initially developed in 2014, DPoS has emerged as a prominent evolution of the PoS model.
2.4.7 Leased Proof of Stake (LPoS) [22] [23] [24]
LPoS, or Lease Proof of Stake, is an advanced version of Proof of Stake that addresses its uncertainties by introducing a leasing option This innovative approach enables nodes with lower balances to participate in the block verification process by leasing resources from wealthier nodes As a result, a dynamic flow within the network is created, increasing the likelihood of less affluent nodes successfully solving blocks The rewards earned from this collaboration are shared with the lessors, incentivizing nodes to maintain a higher rental balance for better chances of being selected for block generation Ultimately, this leasing mechanism promotes decentralization, ensuring that no single entity can dominate the network.
2.4.8 Proof of Elapsed Time (PoET) [25]
The Proof of Elapsed Time (PoET) is a consensus mechanism developed by Intel to enhance energy efficiency and reduce resource wastage It utilizes specialized hardware to foster decentralization and limit collaboration PoET establishes consensus by randomly selecting block leaders, ensuring that all nodes in the network have an equal probability of being chosen as winners.
2.4.9 Practical Byzantine Fault Tolerance (PBFT) [26] [27]
The Practical Byzantine Fault Tolerance (PBFT) mechanism has emerged as an effective solution for addressing Byzantine errors, leading to its adoption in various consensus protocols PBFT operates by defining new blocks in each round, organizing transactions based on their sequence Each node undergoes three distinct stages—prepare, prep, and commit—once it has received verification from at least two-thirds of the participating nodes in the blockchain network Unlike other blockchain systems, Hyperledger integrates PBFT as a Distributed Ledger Technology (DLT) solution, enabling it to effectively manage scenarios involving more than one-third of malicious nodes.
Figure 14 - Transaction flow for PBFT consensus (Hyperledger Foundation, 2020)
Blockchain (DLT) comparison study
Blockchain technology is primarily divided into two categories: permissionless and permissioned Numerous studies aim to compare these types to identify the most suitable blockchain platforms for specific business applications Due to the complexity and scalability of various blockchain projects, there is no straightforward methodology for determining the best option among the numerous active platforms available Relying solely on research publications and technical whitepapers from blockchain developers is not exhaustive, as many projects are still in early development stages or nearing obsolescence Therefore, evaluating active blockchain project websites for updates on ecosystem performance, development progress, community engagement, and long-term support (LTS) is crucial for informed decision-making This thesis focuses on popular open-source permissioned blockchain platforms, excluding permissionless or commercial options from the analysis.
Permissionless blockchains serve as public platforms that have gained significant traction in the crypto community over the past decade These popular blockchains allow anyone to join, ensuring an inclusive environment, while also maintaining user anonymity and privacy.
Permissionless blockchains such as Bitcoin and Ethereum utilize native cryptocurrencies, which are "mined," or transaction fees (gas), to create economic incentives that compensate for the unique costs associated with participation This system relies on the Byzantine Fault Tolerance (BFT) consensus protocol, as outlined in Chapter 2.
Permissioned blockchains, distinct from permissionless ones, utilize Distributed Ledger Technology (DLT) to facilitate interactions among a known group of participants, typically organizations governed by a trust-based model These blockchains enable collaboration among entities with shared goals while maintaining a level of trust, even when full trust isn't established By employing consensus protocols such as Crash Fault Tolerance (CFT) or Byzantine Fault Tolerance (BFT), permissioned blockchains eliminate the need for mining, as seen in Bitcoin or Ethereum In a public permissioned blockchain, a select number of organizations can write to the ledger, while others may only access read permissions This structure minimizes the risk of malicious code being introduced, as participants are identifiable, and all actions—ranging from transaction submissions to smart contract deployments—are recorded according to predefined governance policies, allowing for accountability and resolution of incidents.
2.5.1 Open-source Blockchain (DLT) platforms
The growing popularity of Blockchain (DLT) has led to its adoption across various industries, including retail, banking, finance, manufacturing, and automotive, with a notable emphasis on permissioned blockchains like Hyperledger Fabric These technologies facilitate cross-organizational processes, enhancing transparency, immutability, and trust, which in turn boosts efficiency and revenue for businesses DLT operates as a shared, validated, and updated ledger, ensuring secure and tamper-proof record-keeping The introduction of smart contracts has revolutionized DLTs, promoting a programmable economy and improving reliability and accountability in trading applications Various blockchain platforms have emerged to support smart contracts and provide enterprise solutions, showcasing features like decentralization, security, and data immutability While most DLT platforms exhibit similar capabilities, the choice of the appropriate platform depends on the specific system requirements of the blockchain application This thesis focuses on permissioned blockchains, referencing a comprehensive comparison of open-source platforms, including Hyperledger Fabric, Ethereum, Corda R3, and others.
Kample et al [66] identify key sound features that influence evaluation, including simplicity, cost, community size, ease of use and learning, support levels, performance, security, availability of training materials, reputation, historical context, update frequency, and the capability for advanced feature development such as APIs and web support Additionally, the type of software license, whether open source or proprietary, plays a crucial role in this assessment.
Nanayakkara et al explored the critical factors for evaluating blockchain platforms suitable for private companies, utilizing the Simple Multi-Attribute Rating Technique (SMART) for measurement They emphasized the need for a Multi-Criteria Decision Making (MCDM) method that is straightforward, effective, and appropriate for peer review participants Despite the potential bias associated with SMART, the collective evaluation by multiple peers mitigates this issue, making it a viable choice for selecting an optimal blockchain platform The evaluation process using SMART involves several steps: identifying alternative options, determining criteria, assigning weights to each criterion, and providing final values for each blockchain platform.
Simplicity It means how easy and straightforward a system can be developed using it
Analyzing past developers' insights and the platform's architecture will help assess the simplicity factor to some degree However, a comprehensive understanding of simplicity can only be achieved through the development of a sample project.
When evaluating costs, it is essential to distinguish between initial costs and operational costs Operational costs encompass software license fees, system maintenance fees, and platform usage charges, including gas prices associated with blockchain platform usage Additionally, development costs can vary based on factors such as simplicity and ease of learning Therefore, for a comprehensive evaluation, it is crucial to focus primarily on operational costs.
Analyzing various sources such as websites, reports, social media, and electronic articles helps determine the size of a community This evaluation also includes interest groups, companies, industry branches, partner lists, and client counts to provide a comprehensive understanding of community dynamics.
Ease of use in blockchain platforms is influenced by the existing applications built on the platform and the product's technical capabilities Additionally, ease of learning is determined by simplicity and the availability of commonly known programming languages The choice of programming language is crucial, as platforms that support widely used languages facilitate a faster and more convenient development process for system developers.
Level of support Level of support from a company or community is essential for the adaptation of new technology
The consensus mechanism is a crucial aspect of blockchain technology, encompassing the processes involved in approving and confirming transactions This algorithm ensures that all nodes in the network reach an agreement on the blockchain's contents Blockchain networks can be categorized into three types based on their access privileges and structure: permissionless public networks, permissioned private networks, and consortium networks.
Performance Performance of most of the blockchain platforms depends on its consensus algorithm
Security Blockchain technology provides better security compared to traditional software applications However, there are some significant differences between permissioned and permissionless blockchain networks
Availability of training and learning materials
Access to training and learning materials is crucial for less experienced teams to effectively adapt to new technology Depending on the project team's experience and maturity, this factor may be included or omitted from the project plan.
Reputation Reputation is an important parameter when evaluating a new product, it relates to the reputation of the organization behind the blockchain platform development
Most blockchain platforms operate under well-known open-source licenses like Apache, GNU GPL, GNU AGPL, and MIT These licenses offer significant freedom, particularly in terms of modifying the source code and customizing the original blockchain platform as needed.
API support is essential for enterprise systems as they must interact with various systems and technical stacks Additionally, access to blockchain data is exclusively facilitated through APIs due to its unique data storage structure Consequently, APIs play a crucial role in the development of effective enterprise systems.
The frequency of updates, how recently a newer version is released, and availability of the LTS version are key sub-factors under reputation
Hyperledger Foundation overview
The Hyperledger Foundation, hosted by The Linux Foundation, is a global open-source initiative aimed at advancing cross-industry blockchain technologies It brings together leaders from various sectors, including finance, banking, IoT, supply chain, manufacturing, and technology The Hyperledger ecosystem is characterized by a modular and extensible design philosophy, prioritizing interoperability and highly secure solutions Notably, it adopts a token-agnostic approach, lacking a native cryptocurrency, while promoting the development of a user-friendly API Its common architecture has identified key components for business blockchain applications.
Consensus Layer: responsible for generating an agreement on the order and confirming the correctness of the set of transactions that constitute a block
Smart Contract Layer: responsible for processing transaction requests and determining if transactions are valid by executing business logic
Communication Layer: responsible for peer-to-peer message transport between the nodes that participate in a shared ledger instance
Data Store Abstraction: allows different data-stores to be used by other modules
Crypto Abstraction: allows different crypto algorithms or modules to be swapped out without affecting other modules
Identity Services facilitate the creation of a trusted foundation when setting up a blockchain instance, overseeing the enrollment and registration of identities or system entities throughout network operations They effectively manage changes such as additions, deletions, and revocations while also providing essential authentication and authorization functions.
Policy Services oversees the management of diverse policies outlined in the system, including endorsement, consensus, and group management policies It collaborates with and relies on other modules to effectively implement these policies.
APIs: enables clients and applications to communicate to blockchains
Interoperation: supports the interoperation between different blockchain instances
The consensus component in Hyperledger Foundation projects ensures a reliable ordering of transactions and validates blocks through a network of nodes It serves three core functions: confirming the correctness of transactions in a proposed block based on endorsement and consensus policies, achieving agreement on the order and correctness of transactions to establish a global state, and relying on the smart contract layer to verify the accuracy of the ordered transactions Various consensus algorithms, including Proof of Elapsed Time (PoET), Proof of Work (PoW), Practical Byzantine Fault Tolerance (PBFT), and Raft, are implemented to meet diverse network requirements and fault-tolerance models.
The consensus process begins by receiving transactions from clients, relying on an ordering service to organize them This service can be centralized for development or utilize distributed protocols to address network failures across various nodes To maintain transaction security, the ordering service may not identify transaction content, allowing for hashing or encryption It collects transactions based on consensus algorithms and configurable policies that set time limits or transaction quantities For efficiency, the service often groups multiple transactions into a single block, requiring clear communication of their order Validation of transactions is achieved through the smart contract layer, which enforces the business logic determining transaction validity.
Figure 17 - Generalized Hyperledger consensus process flow (Hyperledger Foundation, 2017)
The smart contract layer ensures that each transaction adheres to the specified policies and contracts, rejecting any invalid transactions from being included in a block The consensus layer relies on the communication layer to interact with clients and peers within the network Various methods can achieve consensus, with the Hyperledger Foundation ecosystem showcasing distinct approaches across its frameworks Each framework executes two primary operations—arranging and validating transactions—allowing for compatibility with any Hyperledger consensus module through logical separation of these processes.
Hyperledger's ecosystem features three active projects: Fabric, Besu, and Sawtooth, with Fabric being the most popular and actively developed, currently at version 2.2 and backed by numerous successful case studies Hyperledger Besu is an open-source Ethereum client, developed under the Apache 2.0 license and written in Java, capable of operating on the Ethereum public network, private permissioned networks, and test networks like Rinkeby, Ropsten, and Gorli, while supporting multiple consensus algorithms such as PoW, PoA, and IBFT Additionally, Hyperledger Sawtooth is a distributed ledger technology (DLT) that accommodates various consensus mechanisms, including Practical Byzantine Fault Tolerance (PBFT) and Proof of Elapsed Time (PoET), with its latest release being version 1.2.
Hyperledger Fabric technical view
Launched in 2018, Fabric is an enterprise-grade distributed ledger platform that emphasizes flexibility and modularity, making it suitable for various industry applications Its modular architecture allows for customization to meet diverse use cases, as detailed in its whitepaper.
Fabric is a versatile distributed ledger technology (DLT) that supports diverse enterprise use cases through its plug-and-play components, including consensus, privacy, and membership services Developed since 2015, it offers a solution characterized by confidentiality, resiliency, flexibility, and scalability, utilizing a modular architecture for distributed application programming and smart contracts As an open-source permissioned blockchain, Fabric stands out from other solutions by providing an elastic and extensible architecture tailored for private enterprises Its modular consensus protocols enable customization to specific use cases and trust models, while the permissioned model enhances security through a membership concept that integrates with industry-standard identity management systems.
According to the Hyperledger Foundation wiki, Fabric has been successfully implemented in over 400 projects across various sectors, including trading, supply chain, and healthcare, as detailed in Chapter 4.
The next part will discuss further the technical design of Fabric and explore a sample transaction flow to indicate the Fabric features
3.2.1 Fabric architecture and main components
The design of a permissioned blockchain for various industries emphasizes a consortium model, involving multiple organizations that collaborate within a decentralized network This architecture prioritizes privacy and identity, featuring a modular setup that allows for flexible integration of components like membership and consensus services Each participating organization plays a distinct role and manages different nodes within the network A critical element of this framework is the defined channel, which acts as a subnet that isolates state and smart contracts, ensuring that all peers within the channel have access to shared data while restricting access outside of it.
Figure 18 - Hyperledger Fabric architecture (Hyperledger Foundation, 2017)
3.2.1.1 The execute-order-validate flow
Figure 19 – The Execute-Order-Validate (Hyperledger Fabric whitepaper, 2018)
Many blockchain platforms, particularly traditional ones, adhere to a standard order-execution flow design In contrast, Fabric employs a unique execution-order-validation model that deviates from this conventional approach This innovative design is structured into three distinct phases: execution, ordering, and validation.
Figure 19 According to the Fabric whitepaper [82], the flow with main steps is described below
In the execution phase, a client initiates a transaction proposal to one or more endorsers, who then simulate the proposal using their local blockchain state without synchronizing with other peers Each endorser generates a writeset, indicating state updates, and a readset, reflecting version dependencies Following the simulation, the endorser issues a cryptographically signed endorsement containing the simulated readset and writeset, which is sent back to the client as a proposal response The client then collects a predetermined number of endorsements according to the endorsement policy and verifies that all endorsers have produced consistent execution results.
If so, it then follows to create the transaction and passes it to the ordering peers which are responsible for the ordering service
In the ordering phase, the orderer collects all transactions submitted by the client and creates a comprehensive order of these transactions Subsequently, these transactions are organized into blocks, forming a hash-chained sequence that encapsulates the transaction data Finally, the orderer broadcasts these blocks to both endorsing and non-endorsing peers It is important to note that orderers do not retain any state of the blockchain, nor do they validate or execute transactions.
In the validation phase (phase 3), after the ordering service concludes, both endorsing and non-endorsing peers receive the produced block and begin evaluating the endorsement policy This evaluation determines the validity of the endorsement created by the endorser; if deemed invalid, the transaction is disregarded Following this, a read-write conflict check is performed, comparing the versions of keys in the readset with the current state of the ledger If discrepancies are found, the transaction is also marked as invalid Once these checks are complete, the ledger update phase commences, appending the block to the blockchain and updating the world state Notably, the blockchain retains records of all transactions, including invalid ones, which distinguishes it from Bitcoin and Ethereum, where only valid transactions are stored.
The Fabric network operates as a permissioned blockchain, comprising nodes that provide ledger and smart contract (chaincode) services to applications Smart contracts generate transactions that are distributed to peer nodes, where they are immutably recorded on the ledger Each node in the network has a unique identity managed by a modular membership service provider (MSP) and assumes one of three roles: Clients submit transaction proposals and manage their execution, Peers execute and validate these proposals while maintaining the blockchain ledger, and Ordering Service Nodes (OSN) establish the total order of transactions without engaging in execution or validation This modular design of consensus in Fabric simplifies the replacement of consensus protocols and enhances overall network efficiency.
Figure 22 - Hyperledger Fabric network (Hyperledger Fabric whitepaper, 2018)
A channel is a private communication subnet within a network, enabling confidential transactions among specific members, defined by organizations, anchor peers, shared ledgers, chaincode applications, and ordering service nodes Transactions occur on a channel where participants must be authenticated and authorized, with each peer receiving a unique identity from a membership services provider (MSP) A Fabric network can support multiple blockchains, or channels, connected to the same ordering service, allowing for distinct peer memberships and separate transaction orders While channels can partition the blockchain's state, consensus is not coordinated across them Trusted deployments may implement by-channel access control for peers The network serves as the technical infrastructure for ledger and smart contract services, with smart contracts generating transactions that are immutably recorded on each peer's ledger Typically, multiple organizations form a consortium to create the network, with permissions governed by agreed-upon policies that can evolve over time.
Figure 23 blow depicts a sample of a Fabric network with most of the main components and brief corresponding explanation of each item in the Fabric network
[96] including organization, network, channel, peer, ledger, smart contract, ordering service, and application clients
Jointly decided, and written into an agreement, that they will set up and operate a Fabric network
Organization R1 offers a client application that facilitates business transactions exclusively within channel C1 In contrast, Organization R2 provides a versatile client application capable of executing transactions in both channel C1 and channel C2 Meanwhile, Organization R3 specializes in a client application that operates solely within channel C2.
Peer nodes in the network, including P1, P2, and P3, manage different copies of ledgers Specifically, peer node P1 holds a copy of ledger L1 linked to C1, while peer node P2 maintains both a copy of ledger L1 associated with C1 and ledger L2 associated with C2 Additionally, peer node P3 is responsible for a copy of ledger L2, which is related to C2.
Peer nodes serve as the essential components of the network, hosting copies of the blockchain ledger For instance, P1's role in the network is to maintain a copy of the ledger L1, making it accessible to other nodes While L1 is physically stored on P1, it is logically connected to the channel C1, facilitating seamless access and interaction within the network.
A crucial aspect of configuring peer P1 is its X.509 identity issued by CA1, linking it to organization R1 When the R1 administrator adds peer P1 to channel C1, P1 begins retrieving blocks from orderer O4 The orderer references the channel configuration CC1 to establish P1's permissions, which are dictated by policies within CC1 that specify whether P1 or organization R1 has the rights to read or write on channel C1.
NC4 The network is governed according to policy rules specified in network configuration NC4, the network is under the control of organizations R1 and R4
Channel C1 operates under the policy rules outlined in configuration CC1 and is managed by organizations R1 and R2 Similarly, Channel C2 is governed by the policy rules specified in configuration CC2 and is controlled by organizations R2 and R3.
Vissan demo implementation
This section showcases the demonstration of Vissan's product origin traceability system, featuring an innovative process flow for both the manufacturing side (Organization A) and the selling side (Organization B) as outlined in Chapter 1 The system is built on Fabric v1.4, which ensures high stability and quality testing, and is deployed within the AWS cloud environment, utilizing AWS networking for optimal performance.
The proposed technical architecture is below to illustrate the implementation for 2 organizations, 2 orderers, 4 peers, and 1 channel above
Figure 28 – The demo architecture with 2 orgs, 4 peers, 1 channel
- 6 instances of t3.medium (2 vCPUs, 4GB) for 2 orderers, 4 peer nodes
- 1 instance of t3.medium (2 vCPUs, 4GB) for the explorer
- 2 instances of t3.small (2 vCPUs, 2GB) for 2 front-end apps simulating the roles of manufacturing side (worker, inspector) and selling side (worker, seller)
The manufacturer organization is set up with 2 peers, and users are created to operate the manufacturing steps including:
Normal user, worker role: the user to update the product status at the step of
“produce” products (“S n Xu t”) and “ship” them (“Giao Nh n”) after products are inspected
Normal user, inspector role: the user updates the product status at the step of
“inspecting” products (“Ki m Kê & Gi t M ”) before shipping products to the Seller
The seller organization is set up with 2 peers, and users are created to operate the retailing steps as below:
After receiving products from the manufacturer, the normal user in a worker role is responsible for updating the product status during the "stock" phase and the "pick & pack" process This includes labeling the products before they are sold to customers.
Normal user, seller role: the user to update the product status at the step of
“sell”products (“Bán Hàng”) when selling the products to customers.
When users log in through the designated frontend application, they submit transactions to the blockchain network, which then updates the product status and relevant data as immutable entries on the ledger The smart contract is created in accordance with Fabric’s chaincode conventions, ensuring that the status updates are executed seamlessly from implementation to deployment, thereby maintaining the integrity of the product state throughout the entire process.
Figure 29 – The smart contracts to save product status to the ledger
The typical smart contract code illustrates the initialization, invocation, and updating of product states on the ledger, following a defined process flow Additional configurations for peers, orderers, members, Certificate Authorities (CA), and Membership Service Providers (MSP) are managed in the AWS cloud Once the smart contract is successfully deployed, it can be invoked by frontend applications connected to the channel When these applications request transaction submissions to update product statuses, the smart contract executes and updates the corresponding product data on the ledger.
The Hyperledger Explorer tool is designed to provide insights into the underlying blockchain system, showcasing elements such as orderers, peers, channels, blocks, and transactions A detailed demonstration of the process flow and functionality of the Hyperledger Explorer is presented in the thesis's demo session.
This demo showcases the functionality of updating the ledger with product statuses throughout the novel process flow, from manufacturing to sales The subsequent analysis will delve into the performance of various versions of Fabric, drawing on technical experiments from existing studies that have demonstrated remarkable concurrency rates, ranging from 1,000 TPS to over 20,000 TPS, across different Fabric deployments.
Hyperledger Fabric adoption (up to mid-2022)
With backing from major industry players in finance, manufacturing, logistics, and security consulting, Hyperledger Fabric has emerged as a cost-effective operating model, particularly known for its permissioned chain framework This versatile technology finds applications across various sectors, including finance, trade logistics, foreign exchange netting, food safety, contract management, diamond provenance, reward point management, low liquidity securities trading, identity management, and digital currency settlements Numerous organizations, such as Sony, Hitachi, Bosch, and Walmart, have successfully integrated Fabric into their operations, showcasing its effectiveness through various case studies As of mid-2022, a diverse range of industries continues to leverage Hyperledger Fabric to enhance their operational efficiency.
• Land and Property Management/ Real Estate Transactions
• Green Assets Management/ Digital Assets
• Financial Services /Trade Finance/ Letters Of Credit
The Fabric platform's modular and versatile design effectively addresses a wide range of industry use cases, thanks to its unique consensus approach that balances performance and privacy Numerous case studies demonstrate Fabric's success across various business domains, affirming its status as an enterprise-grade permissioned blockchain solution This makes it an ideal fit for Vissan, enabling improved product origin traceability in a multi-actor process, which enhances trust in quality and provenance Ultimately, Fabric helps Vissan boost revenue and operational efficiency, supporting the company's growth and financial objectives outlined in Chapter 1, Part 1.3.
Hyperledger Fabric performance and benchmark
When evaluating blockchain performance, it is crucial to consider factors from development to deployment, as ongoing maintenance costs can be substantial once the system is operational with high data and transaction volumes Conducting a comprehensive performance review of blockchain platforms is challenging due to the complexities and scalability issues inherent in decentralized systems Key considerations include transaction size, ordering services, consensus implementation, networking, hardware specifications, the number of nodes, and channel configurations, as highlighted in the Fabric whitepaper.
Research conducted by [103] examined the performance and scalability of Fabric through experiments that considered various factors, including network architecture, endorsement policy, database location, hardware sizing, block size, block time, and I/O-heavy workloads in business logic Additionally, studies such as those by Khan et al [104] have further investigated Fabric's performance specifically for small and medium enterprises.
Table 7 - Fabric performance studies on many versions
[105] 1.4 Present the latency performance modeling and analysis for Fabric blockchain network Focused on the latency of Fabric and proposed a new framework to measure the latency
The performance analysis of the Fabric platform, particularly in version 1.4, utilizes a hierarchical model approach, focusing on two critical factors: ignored block timeout and transaction endorsement failure This analysis introduces a structured transaction mechanism designed to enhance the efficiency and reliability of the Fabric network.
This article presents a comprehensive performance characterization and bottleneck analysis of Fabric, evaluating its efficiency based on the new architecture Each process was meticulously assessed across the execute, request, and validate phases to identify potential performance issues.
This article presents a performance model of the Practical Byzantine Fault Tolerance (PBFT) consensus process specifically for permissioned blockchain networks utilizing Fabric It investigates how the PBFT consensus mechanism influences peer evaluation performance, particularly in scenarios involving a large number of peers within an Internet of Things (IoT) system.
[109] 1.0 Investigated the impact of consensus protocol in HLF performance evaluation Proposed a novel method to evaluate the performance of consensus algorithms in the permissioned blockchain
[110] 1.0 Investigated the possibilities of customizing the blockchain networks for the needs of the applications
[111] v0.6 Present a methodology for evaluating the performance of Ethereum and
Fabric The research team eventually derives performance figures for execution time, latency, and throughput, also considering different workloads
[112] v1.1 Present the execute-order-validate blockchain architecture of Fabric v1.1.0
The research team examines the throughput and latency under consideration of various parameters, such as block size, number of vCPUs, and number of peers
[113] v1.0 Use Caliper to examine the performance of Fabric v1.0 The authors consider various impacting factors, such as the number of nodes, endorsement policy, block size, and transaction size
Blockbench is the first systematic benchmarking framework designed specifically for permissioned blockchains, enabling performance evaluation of private Ethereum implementations (such as Geth and Parity), as well as Fabric and Quorum Utilizing this framework, the authors conduct a comparative analysis of the performance metrics between Fabric and Ethereum.
[116] v1.0 Present a method for evaluating the performance of consensus algorithms in
Ethereum and Fabric The authors eventually derive performance figures for latency and throughput, taking also varying workloads into consideration
The study evaluates the performance of Fabric v1.0 against v0.6, focusing on key metrics such as execution time, latency, and throughput Additionally, it investigates the scalability of both implementations by varying the number of nodes.
In Fabric v1.1, an analysis was conducted on the effects of block size, endorsement policy, channels, and state database selection, leading to the identification of performance bottlenecks The findings prompted the proposal of optimizations that were subsequently integrated into later versions of Fabric.
[119] v1.4 Deploy the Caliper benchmarking tool to examine the performance of Fabric regarding throughput, response time, and simultaneous transactions
Utilize a tailored version of the Caliper benchmarking framework to analyze the impact of sub-second network delays on Fabric's performance The testing environment consisted of two cloud instances located in Germany and France, facilitating the creation of the Fabric network.
The authors assess the performance of Fabric by experimenting with different network configurations to measure key metrics such as throughput, latency, and error rate, while also evaluating the platform's overall scalability They contextualize their findings by comparing them to previous versions of Fabric.
The research focuses on the application of blockchain technology in cross-border e-government services, specifically analyzing the performance of Fabric A key aspect of their investigation is the impact of network delay on Fabric's overall performance.
The performance of Fabric v1.4 is evaluated through horizontal scaling, by adding more nodes, and vertical scaling, by adjusting the number of CPUs per node Based on these evaluations, the authors suggest an optimization for the Fabric architecture that incorporates pipelined execution during the validation and commit phases.
[124] v1.4 Analyze the detail about the performance of Fabric and especially shows the performance of different ordering services For this purpose, a network with
20 machines is used, and the different phases of the transaction flow and endorsement policies are considered
In Fabric v1.4, a theoretical analysis framework was developed to evaluate its performance by incorporating the execute-order-validate logic A series of experiments were conducted to compare the experimental results with simulations, thereby validating the theoretical model.
Guggenberger et al [103] designed a test harness featuring a default configuration of 8 peers, 4 orderers, and 16 clients within a single-channel network utilizing Raft consensus on Fabric v2.0 Their extensive experiments spanned nearly 2,000 hours and involved the establishment of about 1,500 Fabric networks, encompassing roughly 20,000 nodes and 40,000 clients, while processing over 200 million transactions in an AWS cloud environment The paper provides a summary of categorized benchmark factors along with relevant observations.
Table 8 - Benchmark factors and observations
Architecture Number of organizations, peers, and orders
The number of orderers does not significantly affect overall performance for transactions per second (TPS) rates of 1000 and below In small networks, maintaining a constant endorsement policy while adding peers enhances performance Although the number of organizations has a minimal impact on networks with 32 or fewer organizations, its influence grows in larger networks due to the mechanics of gossip dissemination.
Blockchain (DLT) enablement analysis
The implementation of the proposed Blockchain (DLT) solution utilizing Fabric for product origin traceability at Vissan Company demonstrates significant benefits by meeting the requirements outlined in R1, R2, and R3 from Chapter 1, part 1.3 This innovative application of blockchain technology enhances multi-actor processes, ensuring transparency and reliability in tracking product origins.
Immutability ensures that transaction data remains unchanged, preventing any alterations or tampering This feature enables a reliable trace of product origin throughout the company's value chain, with product statuses accurately recorded in the Fabric, assuming that data from previous steps has been securely saved.
Traceability ensures product origin data is accurately documented, detailing every stage from manufacturing to distribution and sales This comprehensive tracking of a product's journey enhances transparency and accountability, allowing consumers to understand the source of their purchases.
- Provenance: the Vissan product data at each transaction point in the value chain are populated to the blockchain network, securing the product provenance up queries
- Smart contract: the business logic among the parties is programmed in chaincode, then deployed, and executed on peer nodes in the blockchain network
- Transparency: the product data is visible and accessible to the parties or users in real-time with recorded transactions based on the consensus mechanism (Raft)
Distributed Ledger Technologies (DLTs) utilize a variety of security measures, including Managed Service Providers (MSP), Certificate Authorities (CA), digital signatures, and cryptographic keys, to safeguard data privacy Additionally, with the support of Fabric for private data on a channel, the integrity of data privacy is effectively maintained.
- Auditability: the blockchain data in Fabric is highly visible across the value chain, making it auditable and increasing its audibility and efficiency upon being audited
- Decentralized database: the Fabric data is not stored on a centralized server but distributed across different nodes in the blockchain network; data access is provided to the relevant parties (organizations)
- Secured database: The data in blockchain data is tamper-proof and impossible to manipulate thanks to the Fabric feature
Enhanced risk management is achieved through instantaneous transaction settlements, allowing organizations involved with Vissan to focus less on product origins during incidents This advancement significantly reduces the risk of counterfeit products, ensuring greater safety and reliability in the supply chain.
- Reduced transaction cost: the transaction costs are less due to the removal of the value chain intermediaries and the silos in the chain.
Hyperledger Fabric security analysis
While Hyperledger Fabric enhances security, careful configuration and monitoring are essential to ensure secure deployments Operators must be aware of various threats unique to permissioned blockchains, which differ from those in permissionless networks, such as the reduced risk of 51% attacks and network partitioning due to known and monitored participants This article examines security threats related to consensus, Membership Service Provider (MSP), and smart contracts, utilizing the STRIDE model for analysis Additionally, the Vissan security center's daily operations should include monitoring and logging threat indicators for prompt identification and remediation Given that Fabric is still evolving, potential untested security vulnerabilities exist, making external security audits or formal verification crucial for sensitive applications to ensure robust system operation.
Network consensus attacks, such as DoS and transaction reordering attacks, pose significant threats The demonstration utilizing Fabric with the Raft consensus algorithm (CFT) indicates a lack of tolerance for malicious actors However, if Fabric were to implement Byzantine Fault Tolerance (BFT) algorithms, it could withstand up to a certain percentage of malicious activity within the network.
The Vissan Security Operation Center (SOC) plays a crucial role in mitigating threats through early detection of malicious behavior, regardless of the consensus algorithm employed By monitoring key indicators such as leadership elections and transaction latencies, the SOC enhances its ability to identify potential risks in consensus processes.
A compromised Managed Service Provider (MSP) poses a serious threat to Vissan's proposed solution, as it can alter network access controls and potentially launch denial-of-service attacks Such compromises may occur due to insider threats or theft of private keys, often remaining undetected until after exploitation has taken place.
To reduce risks, the Vissan Security Operation Center (SOC) should implement best practices for key management, including monitoring certificate creation and revocation This approach is essential for identifying malicious activities in the event of a security breach.
Blockchain platforms, including Fabric, commonly support smart contract execution, particularly in the context of cryptocurrency and decentralized finance (DeFi) While smart contract attacks in DeFi often result in measurable financial losses, similar attacks in Fabric can jeopardize business logic, affecting brand reputation and network performance In addition to typical programming bugs, errors can arise from improper handling of concurrency and nondeterminism Therefore, it is crucial to evaluate smart contract security prior to deployment using analysis tools like the Hyperledger Lab Chaincode Analyzer to identify potential risks.
To reduce the risk of exploitation, it is essential to design and review smart contracts with a focus on security from the beginning, adhering to a secure software development life cycle framework Additionally, the Vissan Security Operation Center (SOC) should actively monitor the performance and usage of deployed smart contracts to identify any anomalous behavior.
STRIDE model analysis
To effectively combat security threats, it is essential to implement proactive measures alongside comprehensive security deployment Detecting many security threats requires the correlation of data from the blockchain network, organizational infrastructure, and threat intelligence providers A critical aspect of this analysis involves utilizing the STRIDE security risk analysis model, which evaluates six key information security risks: Spoofing identity, Tampering with data, Repudiation, Information Disclosure, Denial of Service, and Elevation of privilege Each of these risks addresses specific vulnerabilities, such as unauthorized impersonation, data integrity breaches, unacknowledged actions, unauthorized information exposure, service disruptions, and unauthorized capability enhancements.
With the below analysis and evaluation according to the STRIDE model for the system, we can conclude that the system achieves the desired security requirements
In a hypothetical scenario, an attacker might attempt to spoof a certificate authority account to compromise the system However, this is deemed impossible, as the credential issuer's account can be verified through the X.509 certificate provided by the Fabric certificate authority (CA).
The blockchain's tamper-proof design ensures that once a transaction is recorded in the ledger, it cannot be modified Fabric employs the Elliptic Curve Digital Signature Algorithm (ECDSA) to secure the entire system, encrypting communication throughout the value chain to maintain data integrity, non-repudiation, and privacy As a permissioned platform, Fabric enhances confidentiality through its channel architecture and private data features, allowing participants to create sub-networks where only selected members can view specific transactions This ensures that only nodes within a channel have access to the smart contract and transaction data, preserving privacy and confidentiality Additionally, private data collections among channel members provide similar protections as channels, without the complexity of managing separate channels, further safeguarding against tampering.
Data is digitally signed with the private key linked to the public key in the issuer's X.509 certificate All information published on the blockchain by a Certificate Authority (CA) is consistently monitored and traced back to the identified organization, ensuring that no participant can impersonate them.
In Fabric, the private keys cannot be derived from the public key, ensuring that participants' private keys remain secure This eliminates the risk of exposing private keys, as they are required to be stored in a secure environment.
5.3.1.5 Against Denial of Service (DoS)
Denial of Service (DoS) attacks pose significant threats to the availability of distributed systems, making proactive prevention challenging due to the variety of attack vectors To mitigate this risk, it is essential to gather performance metrics like transaction throughput and latency, which can help identify compromised availability early The Fabric, designed as a distributed system with a microservice architecture and multiple nodes, offers enhanced resilience against DoS threats compared to traditional applications, thereby improving overall network reliability.
The root organization serves as the highest authority within the system, with its rights secured by a digital signature utilizing ECDSA This robust security measure ensures that attackers cannot usurp authority or forge the digital signature, thereby protecting the integrity of the certificate authority in the system.
Conclusion
This study presents a blockchain-based solution for product traceability at Vissan, utilizing a Fabric-based anti-counterfeit management system After a comprehensive analysis of various blockchain platforms, a minimum viable product demo was developed, demonstrating that blockchain technology effectively enhances product traceability within the company's value chain Transactions between manufacturers and sellers are securely recorded on the Fabric blockchain, allowing stakeholders to trace the authenticity of Vissan products This implementation not only ensures data security and immutability but also facilitates third-party arbitration, enabling regulators to monitor any irregularities in the value chain Ultimately, this solution provides robust protection for the Vissan brand, safeguarding its integrity from production to the end consumer.
The proposed system enhances data security by utilizing Fabric blockchain technology, distinguishing it from traditional solutions This study details the technical architecture of Fabric and demonstrates how blockchain enables superior product origin traceability within private companies By implementing smart contracts (chaincode) on the blockchain network, Vissan’s demo system becomes resistant to tampering by malicious actors The system ensures identity verification at every stage of the value chain, effectively preventing counterfeit substitutions during production and sales Additionally, end customers can easily verify the authenticity of Vissan’s products and access data through the blockchain, enhancing transparency and trust.
And with further recommendations to complete the wider scope significantly, the future implementation can:
(a) add and administrate more organizations accordingly to other business aspects such as regulators, financial partners, payment e-wallets, etc
Utilize Fabric's private data and diverse channels to effectively manage product master data, ensuring seamless integration with Vissan's existing ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), and IoT systems for enhanced inclusivity.
(c) also, for some considerations to revoke or to update the product data when incidents happen with the counterfeited or contaminated situations, it is helpful with this feature implemented
(d) in prospects, providing the frontend of mobile or website with QR scan and query for product information is also a good user experience improvement for a completed product origin traceability application
(e) and many more with other features
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Full name: HO ANH THI
Date of birth: 02 / 10 / 1979 Place of birth: Hue City
Address: 1017/48 Hong Bang, Ward 12, District 6, HCMC
1997 - 2003, University of Technology, Bachelor of Engineering, Computer Engineering
2016 - 2018: University of Northampton, Master of Business Administration, Entrepreneurship
2004, Certified Lecturer of Global Aptech Training Center
2007, BEA WebLogic Portal Development Certified
2015, SAP Hybris Ecommerce Platform Certified
2016, SAP Hybris Ecommerce Consultant Certified
2017, Adobe Digital Experience Manager Platform Certified
2020, Thought Machine Core Banking Platform Certified
05/2020 ậ present: Country Head at GFT (Germany)
• Setup the company and grow teams from ground up (presently at 200+ resources)
• Work with headquarter to align the growth strategy for Vietnam in next 5 years
08/2018 ậ 04/2020: Country Head of Technology and Program Management at
• Work and align with Group Technology to oversee local technology, implementation and risk management
• Build cross-functional teams from the ground up to develop products, manage the Vietnam operation and business execution to align with regional strategy
12/2016 ậ 07/2018: Head of Engineering and Delivery at SmartOSC
• Oversee cross-functional activities of delivery and development at the company level for all project models (dedicated teams, fix-priced projects for
Omni-Channel eCommerce, Digital Marketing, Digital Transformation
• Work directly with agencies, partners or customers business & technical teams to build up the engagement
09/2014 ậ 11/2016: Head of Enineering and Delivery at SAI Digital
• Work directly with partners, agencies, customers to provide technical solution proposals, project estimation and schedule to implement
• Lead the consulting activities for solution design, work with Pre-sale team and ODC teams to deliver projects
11/2010 ậ 09/2014: Senior Solution Architect and Enginering Manager at NashTech
• Onsite working directly with technical teams, business teams at customer site to provide design solution and delivery planning
• Manage ODC deliveries from beginning to go live phase
• Lead, direct and communicate vision and mission for project teams
• Work closely with company leaders to provide information regarding performance and development opportunities
06/2009 ậ 11/2010: Senior Solution Architect and Enginering Manager at COA
• Working with Principal Architect team from COA Solution UK
• Manage project development activities and process
• Monitor and control to achieve planned financial objectives for the department
• Manage project plan, task management, and task assignment and delivery 03/2008 ậ 06/2009: Project Lead and Technical Architect at NextVIEW