The RSA algorithm is used to secure data packets are transmit from source node to sink node by powerful clone attack, which can be eliminated by the malicious nodes. The proposed protocol can achieve high clone detection probability using randomly selected trustful witnesses and with larger network lifetime, by effectively distributing the traffic load across the network.
ISSN:2249-5789 Nadiya N et al, International Journal of Computer Science & Communication Networks,Vol 7(3),46-51 Secured Clone Detection using Witness Head Selection to Avoid Malicious Nodes in WSN Nadiya N M.Tech, DCN Department of Telecommunication Engineering Dr AIT, Bangalore nnadiya646@gmail.com Abstract—An energy-efficient location-aware clone attack detection protocol is determined and generally deployed Wireless Sensor Networks, which can certify great clone attack detection The ring structure helps energy-efficient data information, forwarding along the path towards the witness nodes and the sink node The localization information of each sensor node forward its private information to randomly selected witness nodes which are present in a ring structure area to verify the legitimacy of sensor nodes and to report detected clone attacks The RSA algorithm is used to secure data packets are transmit from source node to sink node by powerful clone attack, which can be eliminated by the malicious nodes The proposed protocol can achieve high clone detection probability using randomly selected trustful witnesses and with larger network lifetime, by effectively distributing the traffic load across the network Index Terms—Wireless Sensor Networks, Clone Detection protocol, Energy-memory efficient, Network Lifetime, Secure data I INTRODUCTION Now a day’s world is changing dynamically and Wireless Sensor Networks (WSN) has become an important part of communication media, and it is used for a variety of applications that are military, beginning of environment monitoring, etc., [1], [2], [3] A WSN generally consists of a Base Station and several numbers of sensor nodes Where geographical areas observed by sensor nodes and later these nodes gathers sensor data information The base station is a main for collecting information from sensor nodes throughout wireless media hop by hop Then base station send collected data information to user through the internet Therefore small size and low price of wireless sensors are used to construct large-scale sensor networks Sensors are usually not tamper-proof devices and are deployed in location without monitoring and protection, which makes them susceptible to different attacks [4], [5] Due to the low price of sensor duplication and deployment, attacks have become one of the most critical security issues in WSNs For example, a malicious user may compromise some sensors and take their private information Clone attack is one of most harmful attack is deployment WSN and also is great challenging to determine clone Clone attacks are defined as the malicious user compromises the network sensor node by IJCSCN | June-July 2017 Available online@www.ijcscn.com Prashanth C R Professor Department of Telecommunication Engineering Dr AIT, Bangalore prashanthcr.ujjani@gmail.com utilizing side channel attacking technique adventure the data information on the node After compromising the node, the attacker exploits the confidential information, including secret keys and transfers it on other clone nodes Cloned sensor node can be invested to capture the information of the network region The adversary can also add false information, or manipulate the data information passing through cloned nodes To find efficient clone detection, let us consider a set of sensor nodes that are selected from the network, which is known as witnesses, with the help of the witness nodes and witness headers to prove the legitimacy of the nodes in the network When any of the sensor nodes in the network want to transmit data, it first sends the request to the witnesses for legitimacy verification Then private information of the source sensor node i.e., identity and the location information are shared with all neighbor sensor nodes, witnesses at the stage of witness selection, and witness nodes will report a detected attack to sink node To achieve successful clone detection, witness selection and legitimacy verification should perform two requirements: 1) randomly selected witnesses; 2) At least one of the witness nodes can successfully receive all the verification messages for clone detection [6] The first requirement is to make it difficult for malicious users or attackers eavesdrop the communication between the current source node and its witnesses so that the attacker cannot make duplicate verification messages The second requirement is to make sure that at least any one of the witnesses can verify the identity of the sensor nodes to find whether there is a clone attack or not To guarantee high clone detection, [7], [8], [9], probability, i.e., the probability that clone attacks can be successfully detected, it is critical and challenging to these requirements in clone detection protocol design In this design, the main aim is to detect clone attacks on WSN and also to control the energy consumption and memory storage of clone detection protocol To achieve high clone detection probability with random witness selection and for making satisfactory network lifetime of WSNs, is determined by using an Energy-efficient Ring based Clone Detection (ERCD) protocol This protocol is applicable to general densely deployed multi-hop WSNs 46 ISSN:2249-5789 Nadiya N et al, International Journal of Computer Science & Communication Networks,Vol 7(3),46-51 and efficient to detect replica location claims being used at two different locations in the network Figure -1 ERCD Protocol design The ERCD protocol consists of two stages: one is witness selection and another one is legitimacy verification In witness selection, each source sensor node randomly mapping function is employed to select its witnesses In the legitimacy verification, witness nodes send verification message along with private information of the source sensor node to its witness headers The witnesses will successfully gain the message and it will forward to its witness header for verification Upon receiving the messages from witness nodes, the witness header compares the source verification messages with pre-stored records If the verification messages be different as of pre-stored records, the clone attack is detected and procedure is triggered as shown in figure-1 The Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) security algorithm are proposed to find security issues in WSN II LITERATURE SURVEY The majority works that are done for clone detection protocols [10], [11], [12], in WSN, Mumtaz Qabulio et al., [13] proposed scheme which uses nodes physical location information or any other complex computational intensive algorithm; it is best suited for memory and computationally constrained sensor nodes Clone detection protocol is classified into two different categories, i.e., centralized and distributed clone detection protocols The centralized protocol is designed with the sink or witnesses that are usually located in the center of each region and store the private information of sensor nodes The source node sends its private information to the sink or witnesses, in which a witness compares the private information of source node with its pre-stored records then it determines whether it’s a clone attack or not Richard Brooks et al., [14] proposed a Random key predistribution seems particularly well suited on Wireless Sensor Network for detecting cloning attacks This protocol compares all keys from Bloom filters is gather key data message from all sensor nodes with a threshold value, and if any key is greater than threshold values then that node is considered as cloned attack and removed from the network Wibhada Naruephiphat et al., [15] design to achieve high successful detecting replica rate with the small amount of communication in Wireless Sensor Networks The proposed Area-Based Clustering Detection (ABCD) method is simple IJCSCN | June-July 2017 Available online@www.ijcscn.com Usually, centralized clone [16] detection protocols have low overhead and running complexity However, the malicious users can eavesdrop the transmission between the sink node and sensors, therefore the security of sensor private information may not be guaranteed Whenever the sensor nodes and the sink are close to each other, sensor nodes will deplete their energy sooner than other nodes and dramatically decreases its network lifetime In a distributed clone detection protocols, a set of witnesses is selected to support every sensor These sensors transmit the data between the sink and sensors from being eavesdropped by malicious users Distributed clone detection protocols consist of three different types for the selection of witnesses, that are: i) deterministic selection, ii) random selection and iii) semi-random selection In the deterministic witness selection, the same set of witnesses for all sensor nodes are chosen based on clone detection protocols like proposed Randomized Efficient and Distributed (RED) protocol Mauro Conti et al., [17] proposed a RED protocol for the detection of node replication attacks In particular, it has introduced the preliminary notion of ID-obliviousness and area-obliviousness that convey a measure of the quality of the node replicas detection protocol; that is, its resilience to a smart adversary The distributed clone detection protocols with random witness selection [6] similar to Line-Select Multicast (LSM) protocols, which are closely related to this project which will enhance the network security Yingpei Zeng et al., [18] to find replica-detection protocols must be, Non-Deterministic and Fully Distributed (NDFD) and fulfill three security requirements on witness selection Based on a random walk, Yingpei Zeng proposed two new NDFD protocols that are Random Walk (RAWL) and Tableassisted Random Walk (TRAWL), fulfilling the requirements while having only common communication and memory overheads Mohammad Y Aalsalem et al., [19] proposed a Random Walked (RAWL) starts with several random walks in a network RAWL is one of the witness nodes based distributed techniques, witness nodes are randomly selected by starting many random walks around the network RAWL has gained high security of witness nodes The enhancement of RAWL protocol is aiming to decrease the communication and memory costs while keeping the detection probability high In random witnesses selection, each sensor is randomly selected its witness so that it is difficult for malicious users to get the information from witnesses This scheme is difficult for the source node to reach its witnesses because the randomness of mapping function is increasing so that it makes a challenge to achieve a high clone detection probability To 47 ISSN:2249-5789 Nadiya N et al, International Journal of Computer Science & Communication Networks,Vol 7(3),46-51 ensure the clone detection probability, LSM lets all the nodes in the route between source and witnesses, store the private information of the source node, which leads to the high requirement of data buffer and energy consumption The clone detection probability with low energy consumption and necessary data buffer storage with random witness selection approach is done successfully using random witness selection Another last distributed clone detection protocols are semirandom witness selection approach is adding the advantages of both deterministic witness and random selection approaches which are proposed as Parallel Multiple Probabilistic Cells (PMPC) Ming Zhang et al., [20] proposed to achieve the high replicas attack probability, considering little energy consumption, and small memory overhead sensor networks which are sensitive This will enable to find replication attacks using four replication detection protocols they are B-MEM, BC-MEM, C-MEM, and CC-MEM Bo Zhu et al., [21] proposed two variants of the Localized Multicast approach for the distributed detection of node replication attacks in wireless sensor networks This approach adds with deterministic mapping to minimize communication and memory storage costs Semi-random witness selection scheme, a deterministic region is generated for the source node according to the mapping function, and then witnesses of the source node will be randomly selected from the sensors in this region However, for each sensor leads to a high overhead and time complexity because of two phase witness selection and randomness of the witnesses The energy consumption and the required buffer storage of such protocols are lower than the random witness selection approach but higher than the deterministic ones Most existing approaches can enhance the effective clone detection which will increase energy consumption and memory storage, which may not consider the energy resource and memory storage for some sensor networks which are restricted Therefore distributed clone detection protocol with random witness selection, is used in our project for the clone detection probability, considering main factors such as energy efficient, low memory capacity and longer network lifetime III PROPOSED SYSTEM Let us consider a network region with an enormous number of wireless sensor nodes and one base station (BS) as they are randomly distributed in the network Let us consider sink node as the origin of the system coordinator The network region is virtually separated into adjacent rings, based on the location of the BS, where the width of each ring is same as the transmission range of sensor nodes The network is densely deployed WSN, i.e., for every node situated in each neighboring ring and for each ring, there are sufficient sensor nodes to develop a routing path across the ring IJCSCN | June-July 2017 Available online@www.ijcscn.com Figure- Workflow model of the proposed clone detection technique The network model is shown above figure-2 can be simply enlarged in the case of enormous number BSs, where different BSs uses orthogonal frequency-division multiple access to communicate with its sensor nodes The task is given to each sensor to achieve data information gathering and clone detection In each sensor data information gathering cycle, the sensors send the gathered data information to the sink node through multi-hop paths using the distance formula Distance formula = Where ( ) and ( ) are the position of two nodes To conduct legitimacy verification, each sensor buffer storage capacity to store the data information Buffer storage capacity should be sufficient to store the private data information of source nodes, in which any node can be chosen as a witness When the buffer storage of the sensor node is full, then its previous data information gets dropped because to accept most recent incoming data information A key pair (a, b) is assigned to every node, where a and b are the node ID and the node 48 ISSN:2249-5789 Nadiya N et al, International Journal of Computer Science & Communication Networks,Vol 7(3),46-51 secret key In the network, all nodes share their ID data information with other nodes The connection key is a compromised by malicious users on either side of the connection is a compromise Every sensor node knows the physical data information and the relative locations of its neighbor nodes, where the relative location refers to the hop distance between a sensor node and the sink, and the hop distance can be obtained by a breadth-first search In project considering a distributed clone detection protocol with random witness selection can achieve superior performance in terms of the clone detection probability, network lifetime with reasonable data buffer capacity which shows simulation results and secure data information by using RSA algorithm, this algorithm included with product of two large prime numbers used to create the public and private key The RSA algorithm is used both encryption and authentication algorithm whereas encryption key is not same as the decryption key The public key (e, N) is a pair number and it can be distributed The private key (d, N) is a pair number and should be kept secret The message can be decrypted by using a private key; this key has been encrypted with the public key Let us consider a small set of nodes is compromised by the malicious users Using the clone detection protocol probability, i.e., the cloned node can be successfully detected, to ensure the security of WSNs Meanwhile to maintain the sufficient energy efficiently and buffer memory storage capacity for data collection and operating clone detection protocol should be guaranteed It means the network lifetime that is the period from the start of network operation until the first outage occurs should not be affected by the proposed clone detection protocol with sensors buffer storage IV ERCD PROTOCOL ERCD protocol achieves high clone detection, longer network lifetime, energy efficient, and limited requirement of buffer storage capacity The ERCD protocol starts with a Perform a breadth-first search by sink node to initiate the ring index All sensor nodes its private information i.e., location and ID information, is shared by all neighboring sensor nodes ERCD protocol consists of two stages: witness selection and legitimacy verification Later, when any one of the sensor node in network establishes a transmission data to other nodes, it first sends the request to witnesses for legitimacy verification within the ring structure, i.e., it has to run ERCD protocol Witness selection, a ring index is randomly chosen by the mapping function as the Witness ring of node ɑ Assist in reducing the traffic load in a hotspot, the area around the sink cannot be chosen by the mapping function Later, node ɑ sends its private information to the node located in witness ring index area, and then the node forwards the information along the witness ring it will form a ring structure The ring index of node ɑ denoted , is compared with its witness ring to decide the next forwarding node The message index will be forwarded to other node located in ring When ; or else, the message will be forwarded to any IJCSCN | June-July 2017 Available online@www.ijcscn.com other node in ring This step is able to forward the message toward the witness ring of node The ERCD protocol repeats above process until a node denoted b, located in the witness ring structure is reached Node b stores the private information of node ɑ and forwards the message to any other node located in ring within its transmission range denoted as c Then, node c stores the information and forwards the message to the node d, where the link (c, d) has the longest projection on the extension line of the directional link from b to c Node b reappears in the transmission range awaiting the procedure will be repeating Therefore, the observer witnesses of node a contain a ring structure, consisting of b, c,…b as shown in Figure-3 Figure-3: Witness Ring In the legitimacy verification, the source node sends its verification message along with private information follows the same path towards the witness ring for the witness selection To enhance the probability that witness nodes can successfully receive the verification message it will forward the message to its witness header for verification The verification message will be broadcast when it is very close to the witness ring, the purpose of declaring, three-ring broadcasts, i.e., the message will be broadcast in , and as shown in Figure-4 So it ensures the network security from the three-ring broadcasts, i.e., let our assumption that all witnesses are trustful for the clone detection probability To determine whether there exist a clone attack or not, all the verification messages received by witnesses are forwarded to the witness header along the same route in witness selection Upon receiving the messages from witness nodes, the witness header compares the source verification messages with pre-stored records If more than one copies of verification messages are received, it results the clone attack is detected and a revocation procedure will be triggered The sensors nodes in the transmission path but not located in the witness ring are called the transmitters Figure-4: Legitimacy Verification The witness header of the source node ɑ, denoted by , is a sensor located in witness ring ; meanwhile, it is also in the communication range of the transmitter located in ring index 49 ISSN:2249-5789 Nadiya N et al, International Journal of Computer Science & Communication Networks,Vol 7(3),46-51 or The witness header is randomly selected by the transmitter in the neighboring witness ring, i.e., the ring of or If witness headers received more than one copies, then ERCD protocol will trigger a revocation procedure; if no copy is received from the source node due to packet loss or silent cloned node, the source node will not be permitted for transmissions An example is shown in Figure-4 Let ɑ and ɑ’ denote the source node and one cloned node The verification messages of both ɑ and are broadcast in ring , and later, the both messages are received by the witness header, and a revocation procedure is triggered V PERFORMANCE ANALYSIS The performance of ERCD protocol is analyzed NS2 open source modular simulation platform As NS2 is a discrete event-driven system, the event set stored in the system and using our ERCD protocol to estimate events are receiving out one at a time in the simulation Let us consider 54 numbers of sensor nodes and with a 600m of the radius in WSN, sensors in the ring-shaped structure The range of each sensor node is 10m In the simulation, verification request messages and data information both are of same size for quality, i.e., 100 bytes Collected data information is followed by each action of witness selection In literature the majority of the works that are selected witness nodes Compare clone detection probability of ERCD and existing protocols [20] with different node density and network scale in Figure-5 ERCD has two main requirements: the first one ERCD protocol has superior performance in achieving high clone detection probability than different protocols, it may find the clone attacks effectively, and second one clone detection probability of ERCD protocol increases with extent of common node degree, because it’s high probability of successfully conduct witness selection Figure-6: Required data buffer by using ERCD or existing protocol Now compare the network lifetime with different numbers of sensor nodes in Figure -7 When sensor nodes close to the sink node are having comparatively heavier traffic load will deplete their energy faster than those far away nodes The traffic load of these sensors will increase dramatically when increasing in the node number, which leads to a much shorter lifetime of those nodes ERCD protocol balances the energy consumption of sensors at different locations and then it distributes the traffic load across the network Hence, the proposed ERCD protocol achieves the best network lifetime amongst the P-MPC protocols, and it does not considerably decrease with the increase of node number as shown in Figure-7 Figure-7: Network lifetime with different node number Further, compare the energy consumption of sensor nodes of ERCD protocol and P-MPC [20] cycles of clone detection and hop length from the sink in Figure-8 The sensor nodes have longer network lifetime it shown in below scenarios by using same time period or location Figure-5: Clone detection probability of ERCD or Existing protocols under different parameter The required data buffer with numerous node densities by using ERCD and existing [20] protocols is compared as shown in Figure-6 ERCD protocol declares the witness nodes within a ring structure; it results in high performance in clone detection as well as data buffer storage by comparing with PMPC protocols IJCSCN | June-July 2017 Available online@www.ijcscn.com Figure-8: Lifetime of sensor nodes with various hop length from the sink 50 ISSN:2249-5789 Nadiya N et al, International Journal of Computer Science & Communication Networks,Vol 7(3),46-51 VI CONCLUSION An ERCD protocol to achieve high clone detection deployed WSN This protocol divided into two main parts one is witness selection and another one is legitimacy verification Simulation results have demonstrated that ERCD protocol can detect the clone attack with almost probability with a set of nodes are selected within ring area, which are called witness nodes, to help certify the legitimacy of the nodes in the network The RSA algorithm is used secure source data packets information from robust clone detection The proposed protocol can also achieve long network lifetime by effectively distributing the traffic load across the network, energy consumption with the reasonable storage capacity of the data buffer In future work, it can consider different mobility patterns under various network scenarios VII REFERENCE [1] R Lu, X Lin, H Zhu, X Liang, and X Shen., “BECAN: A bandwidthefficient cooperative authentication scheme for filtering injected false data in wireless sensor networks,” IEEE Transaction Parallel Distributed System, vol 23, no 1, pp 32–43, Jan 2012 [2] I F Akyildiz, W Su, Y Sankarasubramaniam, and E Cayirci, “Wireless sensor networks: A survey,” Journal on Computer Network, vol 38, no 4, pp 393–422, Mar 2002 [3] A Liu, J Ren, X Li, Z Chen, and X Shen, “Design principles and improvement of cost function based energy aware routing algorithms for wireless sensor networks,” Journal on Computer Network, vol 56, no 7, pp 1951–1967, May 2012 [4] T Shu, M Krunz, and S Liu, “Secure data collection in wireless sensor networks using randomized dispersive routes,” IEEE Transsaction Mobile Computing, vol 9, no 7, pp 941–954, Jul 2010 [5] P Papadimitratos, J Luo, and J P Hubaux, “A randomized countermeasure against parasitic adversaries in wireless sensor networks,” IEEE Journal on Selected Areas Communication, vol 28, no 7, pp 1036–1045, Sep 2010 [6] B Parno, A Perrig, and V Gligor, “Distributed detection of node replication attacks in sensor networks,” in Proceedings IEEE Symposium Security Privacy, pp 49–63, May 8-11, 2005 [7] Y Xuan, Y Shen, N P Nguyen, and M T Thai, “A trigger identification service for defending reactive jammers in WSN,” IEEE Transactions on Mobile Computing, vol 11, no 5, pp 793–806, May 2012 [8] R Lu, X Lin, H Zhu, X Liang, and X Shen., “BECAN: A bandwidthefficient cooperative authentication scheme for filtering injected false data in wireless sensor networks,” IEEE Transactions on Parallel Distributed System, vol 23, no 1, pp 32–43, Jan 2012 [9] J Li, J Chen, and T H Lai, “Energy-efficient intrusion detection with a barrier of probabilistic sensors,” in Proceedings IEEE, pp 118–126, March 2012 [10] R Sivaraj R, and Thangarajan, “Location and Time Based Clone Detection in Wireless Sensor Networks”, IEEE Fourth International Conference on Communication Systems and Network Technologies, pp.133-137, April 2014 [11] A Vanathi, B.Sowjanya Rani, “Cloning Attack Authenticator in Wireless Sensor Networks”, International Journal of Computer Science and Technology, vol.3, issue Spl.5, pp 980-983, March 2012 [12] Neenu George, and T.K.Parani, “Detection of Node Clones in Wireless Sensor Network Using Detection Protocols”, International Journal of Engineering Trends and Technology, vol 8, no.6, pp.286-291, February 2014 [13] Mumtaz Qabulio, Yasir Arfat Malkani, and Ayaz Keerio, “Securing Mobile Wireless Sensor Networks (WSNs) against Clone Node Attack”, IEEE Conference on Information Assurance and Cyber Security, pp.5055, December 2015 [14] R Brooks, P Y Govindaraju, M Pirretti, N Vijsaykrishnan, and M T Kandemir, “On the detection of clones in sensor networks using random key predistribution,” IEEE Transactions on System, Man, and Cybernetics, vol 37, no 6, pp 1246–1258, Nov 2007 IJCSCN | June-July 2017 Available online@www.ijcscn.com [15] W Naruephiphat, Y Ji, and C Charnsripinyo, “An area-based approach for node replica detection in wireless sensor networks,” in Proceedings IEEE Trust, security and privacy in Computing, pp 745–750, June 2012 [16] Shriya V.Autkar, M R Dhage, and S P Bholane, “A Survey on Distributed Techniques for Detection of Node Clones in Wireless Sensor Networks”, IEEE International Conference on Pervasive Computing, pp 1-4, January 2015 [17] M Conti, R D Pietro, L Mancini, and A Mei, “Distributed detection of clone attacks in wireless sensor networks,” IEEE Transaction on Dependable and Secure Computing, vol 8, no 5, pp 685–698, Sep.-Oct 2011 [18] Y Zeng, J Cao, S Zhang, S Guo, and L Xie, “Random-walk based approach to detect clone attacks in wireless sensor networks,” IEEE Journal on Selected Areas in Communications, vol 28, no 28, pp 677– 691, Jun 2010 [19] Mohammad Y Aalsalem, Wazir Zada Khan, and N M Saad, “Detecting Clones in Wireless Sensor Networks Using Constrained Random Walk”, IEEE International Conference on Radar, Antenna, Microwave, Electronics and Telecommunications, pp.55-59, October 2015 [20] M Zhang, V Khanapure, S Chen, and X Xiao, “Memory efficient protocols for detecting node replication attacks in wireless sensor networks,” in Proceedings IEEE 17th International Conference Network Protocols, pp 284–293, October 2009 [21] B Zhu, S Setia, S Jajodia, S Roy, and L Wang, “Localized multicast: Efficient and distributed replica detection in large-scale sensor networks,” IEEE Transaction Mobile Computing, vol 9, no 7, pp 913–926, Jul 2010 51 ... shown in Figure-6 ERCD protocol declares the witness nodes within a ring structure; it results in high performance in clone detection as well as data buffer storage by comparing with PMPC protocols... data information gathering and clone detection In each sensor data information gathering cycle, the sensors send the gathered data information to the sink node through multi-hop paths using the... sends its private information to the node located in witness ring index area, and then the node forwards the information along the witness ring it will form a ring structure The ring index of node