Cloud Computing and Big Data: Technologies, Applications and Security

This book addresses topics related to cloud and Big Data technologies, architecture and applications including distributed computing and data centers, cloud infrastructure and security, and enduser services. The majority of the book is devoted to the security aspects of cloud computing and Big Data. Cloud computing, which can be seen as any subscriptionbased or payperuse service that extends the Internet’s existing capabilities, has gained considerable attention from both academia and the IT industry as a new infrastructure requiring smaller investments in hardware platforms, staff training, or licensing software tools. It is a new paradigm that has ushered in a revolution in both data storage and computation.In parallel to this progress, Big Data technologies, which rely heavily on cloud computing platforms for both data storage and processing, have been developed and deployed at breathtaking speed. They are among the most frequently used technologies for developing applications and services in many fields, such as the web, health, and energy. Accordingly, cloud computing and Big Data technologies are two of the most central current and future research mainstreams. They involve and impact a host of fields, including business, scientific research, and public and private administration. Gathering extended versions of the best papers presented at the Third International Conference on Cloud Computing Technologies and Applications (CloudTech’17), this book offers a valuable resource for all Information System managers, researchers, students, developers, and policymakers involved in the technological and application aspects of cloud computing and Big Data.

Lecture Notes in Networks and Systems 49 Mostapha Zbakh  Mohammed Essaaidi  Pierre Manneback · Chunming Rong Editors Cloud Computing and Big Data: Technologies, Applications and Security Lecture Notes in Networks and Systems Volume 49 Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: kacprzyk@ibspan.waw.pl The series “Lecture Notes in Networks and Systems” publishes the latest developments in Networks and Systems—quickly, informally and with high quality Original research reported in proceedings and post-proceedings represents the core of LNNS Volumes published in LNNS embrace all aspects and subfields of, as well as new challenges in, Networks and Systems The series contains proceedings and edited volumes in systems and networks, spanning the areas of Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems and other Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output The series covers the theory, applications, and perspectives on the state of the art and future developments relevant to systems and networks, decision making, control, complex processes and related areas, as embedded in the fields of interdisciplinary and applied sciences, engineering, computer science, physics, economics, social, and life sciences, as well as the paradigms and methodologies behind them Advisory Board Fernando Gomide, Department of Computer Engineering and Automation—DCA, School of Electrical and Computer Engineering—FEEC, University of Campinas—UNICAMP, São Paulo, Brazil e-mail: gomide@dca.fee.unicamp.br Okyay Kaynak, Department of Electrical and Electronic Engineering, Bogazici University, Istanbul, Turkey e-mail: okyay.kaynak@boun.edu.tr Derong Liu, Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, USA and Institute of Automation, Chinese Academy of Sciences, Beijing, China e-mail: derong@uic.edu Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta, Alberta, Canada and Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland e-mail: wpedrycz@ualberta.ca Marios M Polycarpou, KIOS Research Center for Intelligent Systems and Networks, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus e-mail: mpolycar@ucy.ac.cy Imre J Rudas, Óbuda University, Budapest Hungary e-mail: rudas@uni-obuda.hu Jun Wang, Department of Computer Science, City University of Hong Kong Kowloon, Hong Kong e-mail: jwang.cs@cityu.edu.hk More information about this series at http://www.springer.com/series/15179 Mostapha Zbakh Mohammed Essaaidi Pierre Manneback Chunming Rong • • Editors Cloud Computing and Big Data: Technologies, Applications and Security 123 Editors Mostapha Zbakh ENSIAS College of Engineering Mohammed V University Agdal, Rabat, Morocco Mohammed Essaaidi ENSIAS College of Engineering Mohammed V University Agdal, Rabat, Morocco Pierre Manneback Department of Computer Science Polytechnic of Mons Mons, Belgium Chunming Rong Department of Electrical Engineering and Computer Science University of Stavanger Stavanger, Norway ISSN 2367-3370 ISSN 2367-3389 (electronic) Lecture Notes in Networks and Systems ISBN 978-3-319-97718-8 ISBN 978-3-319-97719-5 (eBook) https://doi.org/10.1007/978-3-319-97719-5 Library of Congress Control Number: 2018950099 © Springer Nature Switzerland AG 2019 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface Cloud computing has recently gained great attention from both academia and IT industry as a new infrastructure requiring smaller investments in hardware platform, staff training, or licensing new software tools It is a new paradigm that has followed grid computing technology that has made a revolution in both data storage and computation Cloud computing can be seen as any subscription-based or pay-per-use service that extends the Internet existing capabilities It can be used as a “software-as-service (SaaS Cloud)” or as a “platform-as-service (PaaS Cloud)” or as an “infrastructure-as-service (IaaS Cloud).” Data-storage-as-a-service (DaaS Cloud) has also emerged in the past few years to provide users with storage capabilities In parallel with this progress, big data technologies have been developed and deployed so rapidly and rely heavily on cloud computing platforms for both storage and processing of data These technologies are widely and increasingly used for applications and services development in many fields, such as Web, health, and energy In other words, cloud computing and big data technologies are considered within the current and future research frontiers They also cover several fields including business, scientific research, and public and private administrations This book addresses topics related to cloud and big data technologies, architectures and applications including distributed computing and data centers, cloud infrastructure and its security, end-user services, big data and their applications Most part of this manuscript is devoted to all security aspects related to cloud computing and big data This book aims to be an up-to-date reference for researchers and end users on all aspects related to cloud computing and big data technologies and application v vi Preface Topics • • • • • • • • • Cloud architecture Mobile computing Green computing Resource allocation HPC GPU Energy efficiency Big data Security and privacy Target Audience Information systems directors, academicians, researchers, students, developers, policy-makers will find this book very useful, through its twenty-four chapters that cover several theoretical and experimental studies and researches in the fields of cloud computing, big data, and security Organization of the book This book covers several concepts and features related to cloud computing and big data theoretical background, technologies, and applications It also addresses some advanced security issues related to them such as data privacy, access control, and fault tolerance It is organized as follows: Chapter presents two highly efficient identity-based signcryption schemes that can be used as a building block for a proxy re-encryption scheme These schemes allow users to store signed and encrypted data in the cloud, where the cloud server provider is able to check the authentication but not to derive the content of the message Chapter presents a thorough study allowing to identify a set of security risks in a cloud environment in a structured way, by classifying them by types of service as well as by deployment and hosting models Chapter proposes a new effective security model for mobile cloud database-as-a-service (DBaaS) in which a user can change his password, whenever demanded Furthermore, security analysis realizes the feasibility of the proposed model for DBaaS and achieves efficiency It also proposes an efficient authentication scheme to solve the authentication problem in MCC Chapter proposes a new scheme that aims to improve FADE security by using Trusted Platform Module (TPM) The proposed scheme provides a value-added security layer compared to FADE with less overhead computational time Preface vii Chapter presents some new approaches for data protection in a cloud and discusses a new secure architecture based on three layers Chapter introduces a middleware solution that provides a set of services for cost-effective management of crowdsensing data for mobile cloud computing Chapter proposes a solution based on fragmentation to support a distributed image processing architecture, as well as data privacy The proposed methods combine a clustering method, the fuzzy C-means (FCM) algorithm, and a genetic algorithm (GA) to satisfy quality of service (QoS) requirements This solution reduces the execution time and security problems This is accomplished by using a multi-cloud system and parallel image processing approach Chapter compares different scenarios of collaborative intrusion detection systems proposed already in previous research work This study is carried out using CloudAnalyst which is developed to simulate large-scale cloud applications in order to study the behavior of such applications under various deployment configurations and to choose the most efficient implementation in terms of response time and the previous parameters Chapter presents a t-closeness method for multiple sensitive numerical (MSN) attributes It could be applied to both single and multiple sensitive numerical attributes In the case where the data set contains attributes with high correlation, then this method will be applied only to one numerical attribute Chapter 10 proposes a conceptual model with architectural elements and proposed tools for monitoring in Real-Time Analytical Processing (RTAP) mode smart areas This model is based on lambda architecture, in order to resolve the problem of latency which is imposed in transactional requests (GAB network) Chapter 11 presents a new noise-free fully homomorphic encryption scheme based on quaternions Trans-ciphering is supposed to be an efficient solution to optimize data storage in the context of outsourcing computations to a remote cloud computing as it is considered a powerful tool to minimize runtime in the client side Chapter 12 designs an approach that embraces model-driven engineering principles to automate the generation of the SLA contract and its real-time monitoring It proposes three languages dedicated, respectively, to the customer, the supplier, and the contract specification by using machine learning to learn QoS behavior at runtime Chapter 13 proposes a new approach for content-based images indexing It provides a parallel and distributed computation using Hadoop Image Processing Interface (HIPI) framework and Hadoop Distributed File System (HDFS) as a storage system, and exploiting graphics processing units (GPUs) high power Chapter 14 draws a new method to classify the tweets into three classes: positive, negative, or neutral in a semantic way using WordNet and AFINN1 dictionaries, and in a parallel way using Hadoop framework with Hadoop Distributed File System (HDFS) and MapReduce programming model It also proposes a new sentiment analysis approach by combining several approaches and technologies such as information retrieval, semantic similarity, opinion mining or sentiment analysis and big data viii Preface Chapter 15 presents parallel and distributed external clustering validation models based on MapReduce for three indexes, namely: F-measure, normalized mutual information, and variation of information Chapter 16 conducts a systematic literature review (SLR) of workflow scheduling strategies that have been proposed for cloud computing platforms to help researchers systematically and objectively gather and aggregate research evidences about this topic It presents a comparative analysis of the studied strategies and highlights workflow scheduling issues for further research Chapter 17 presents different techniques to achieve green computing with an emphasis on cloud computing Chapter 18 exposes a GPU- and multi-GPU-based method for both sparse and dense optical flow motion tracking using the Lucas–Kanade algorithm It allows real-time sparse and dense optical flow computation on videos in Full HD or even 4K format Chapter 19 examines multiple machine learning algorithms, explores their applications in the various supply chain processes, and presents a long short-term memory model for predicting the daily demand in a Moroccan supermarket Chapter 20 evaluates the performance of dynamic schedulers proposed by StarPU library and analyzes the scalability of PCG algorithm It shows the choice of the best combination of resources in order to improve their performance Chapter 21 proposes a machine learning approach to build a model for predicting the runtime of optimization algorithms as a function of problem-specific instance features Chapter 22 formalizes the Web service composition problem as a search problem in an AND/OR service dependency graph, where nodes represent available services and arcs represent the semantic input/output dependencies among these services Chapter 23 presents a text-to-speech synthesizer for Moroccan Arabic based on NLP rule-based and probabilistic models It contains a presentation of Moroccan Arabic linguistics, an analysis of NLP techniques in general, and Arabic NLP techniques in particular Chapter 24 presents a context-aware routing protocol based on the particle swarm optimization (PSO) in random waypoint (RWP)-based dynamic WSNs Mostapha Zbakh Mohammed Essaaidi Pierre Manneback Chunming Rong Acknowledgments The editors would like to thank all of the authors who submitted their chapters to this book We thank also all reviewers for their time and tangible work they have made to successfully complete the reviewing process We also sincerely thank Dr Thomas Ditzinger, Springer Executive Editor, Interdisciplinary and Applied Sciences & Engineering, and Mrs Varsha Prabakaran, Springer Project Coordinator in Books Production Service for the opportunity of having this book, for their assistance during its preparation process and for giving the authors the opportunity to publish their works in Springer Book in LNNS series Many thanks also to the Editorial Board and Springer’s staff for their support Finally, we would like to thank the following Editorial Committee members for professional and timely reviews: Youssef Baddi (Morocco), An Braeken (Belgium), Dan Grigoras (UK), Munir Kashif (Saudi Arabia), Ma Kun (China), Sidi Ahmed Mahmoudi (Belgium), Mahmoud Nasser (Morocco), Yassir Samadi (Morocco), Claude Tadonki (France), Said Tazi (France), Abdellatif El Ghazi (Morocco), Abdelmounaam Rezgui (USA), Helen Karatza (Greece), and Abdellah Touhafi (Belgium) ix ... centers, cloud infrastructure and its security, end-user services, big data and their applications Most part of this manuscript is devoted to all security aspects related to cloud computing and big. .. research, and public and private administrations This book addresses topics related to cloud and big data technologies, architectures and applications including distributed computing and data... theoretical and experimental studies and researches in the fields of cloud computing, big data, and security Organization of the book This book covers several concepts and features related to cloud computing