International Journal of Pure and Applied Mathematics Volume 118 No. 9 2018, 313-329 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu Effectively Suppress the Attack of Sinkhole in Wireless Sensor Network using Enhanced Particle Swarm Optimization Technique N. Nithiyanandam1 Dr. P. Latha Parthiban2 B. Rajalingam3 1,3Research Scholar 2Assistant Professor 1, 2 Department of Computer Science, School of Engineering, 1,2Pondicherry University, Pudhuvai, India 3Department of Computer Science & Engineering, Annamalai University, 3Annamalainagar, Tamilnadu, India [email protected], [email protected], [email protected] Abstract Wireless Sensor Networks (WSN) is an emerging field of research with large number of applications and associated constraints like throughput, network lifetime, overhead, reliability, etc.,. To help in these aspects clustering of nodes, multi-hop transmission routing protocol for enhancing the security of WSN. Clustering the nodes in a network provide an efficient way to easily identify the sinkhole even in large set of network nodes. Grouping the nodes narrow down to identify of suspect or a minimum list of suspected nodes can be easily retrieved in which later we can deploy an identification and mitigation algorithm to find and mitigate the sinkhole. The main objective of research work is to modified flocking based clustering algorithm for node clustering to effectively suppress the attack of sinkhole in Wireless Sensor Network. In this research we propose a Flocking model is described as a group of individuals clustered together in common velocity. It consists of three simple steering rules that need to be executed at each instance over time, which includes: (1) Separation: steering to avoid collision with other boids nearby; (2) Alignment: steering toward the average heading and matching the velocity of its neighbour flock mates; (3) Cohesion: steering to the average position of the neighbour flock mates. This algorithm is designed to provide optimal solution for such large instances. We also show; how our proposed model can handle the routes, transmission delay, clustering, etc without facing any problem of network failure. Keywords: WSN, sinkhole, Enhanced Particle Swarm Optimization, VGM, Particle Swarm Optimization. 1. INTRODUCTION The networks which holds the capability to interface with this real world which is physical in nature with the virtual world in a vast manner and provides reasonable uses and causes for developing application in large number which results in Internet of Things, sixth sense technology, habitat monitoring, sensor based agriculture, etc,. Though it gives enormous benefits it results in challenge in terms of security. Recent advances in communication and computing Wireless Sensor Network gathered high range of attention in terms of research oriented proposals. These security issues in sensors make the researchers to deploy a security mechanism on it and use nature as their test bed to prove the efficiency of their proposed work. At first this WSN has been designed and deployed for military purposes for sensing and reporting of climate and physical changes in their target area. Later due to its advanced techniques it has been deployed throughout the country for commercial and personal purposes. The main problem occurs during the clustering of nodes and while the communication between nodes to reach sinks, there might be congestion in the network due 313 International Journal of Pure and Applied Mathematics Special Issue to traffic like collision between nodes or link failure. In order to avoid those problems bio inspired way of clustering can be implementing to cluster the nodes. Our model achieves two different themes, first an efficient way to form cluster and then to deploy a mitigation algorithm to suppress the sinkhole in Wireless Sensor Network. WSNs are susceptible to a wide class of attacks among which sinkhole attack has been identified as one of the serious threats. In this type of attack, a malicious node advertises itself as a best possible route to the base-station which deceives its neighbours to use the route more frequently. Thus, the malicious node has the opportunity to tamper with the data, damage the regular operation or even conduct many further challenges to the security of the network. An adversary utilizes a compromised node to launch the attack in which a route is advertised to deceive neighbours. Furthermore, the high quality route not only attracts the neighbours of sinkhole but also it attracts almost all the nodes that are closer to the sinkhole than to the base-station (may be from several hops away) which amplifies the threat that depicts a sinkhole attack. Clustering the nodes in wireless sensor network and providing a security mechanism in order to avoid the sinkhole attack are the two set of process which gives the network a greater lifetime and integrity and reliability to the network. (i) Security Goals When dealing with security in WSNs, we mainly focus on the problem of achieving some of all of the following security contributes or services: Confidentiality: Confidentiality refers to data in transit to be kept secret from eavesdroppers. Here symmetric key ciphers preferred for their low power consumption. Integrity: Integrity measures that the received data is not altered in transit by an adversary. Authentication: Authentication enables a node to ensure the identity of the peer with which it is communicating. Availability: The service should be available all the time. Data Freshness: It suggests that the data is recent, and it ensures that no old messages have been replayed. Non-repudiation: It denotes that a node cannot deny sending a message it has previously sent. Authorization: It ensures that only authorized nodes can be accessed to network services or resources. These goals are not ensured by traditional cryptographic techniques. So some new cryptographic measures are needed for sensor network. (ii) Attacks on Wireless Sensor Networks The Sensor networks are self-organizing networks which, once deployed, are expected to run autonomously and without human attendance. Major attacks on sensor networks are as follow: A. Jamming Jamming interferes with the radio frequencies of the sensor nodes. Only a few jamming nodes can put a considerable amount of the nodes out of order. If the adversary can block the entire network then that constitutes complete DoS. B. Tampering 314 International Journal of Pure and Applied Mathematics Special Issue A tampering attacker may damage a sensor node, replace the entire node or part of its hardware or even electronically interrogate the nodes to gain access to sensitive information, such as shared cryptographic keys and how to access higher communication layers. C. Spoofed, altered or replayed routing information This is the most direct attack. By spoofing, altering or replaying routing information the attacker can complicate the network and create routing loops, attracting or repelling traffic, generating false error messages, shortening or extending source routes or partitioning the network. D. Selective forwarding In such an attack the adversary includes itself in a data flow path of interest. Then the attacker may choose not to forward certain packets and drop them causing a sort of black hole. E. The Sybil Attack A malicious node present multiple identities to the network is called Sybil attack. This attack is especially confusing to geographic routing protocols as the adversary appears to be in multiple locations at once. F. Wormholes In these attacks the adversary tunnels messages received in one part of the network over a low latency link, to another part of the network where the messages are then replayed. Wormholes often convince distant nodes that they are neighbors, leading to quick exhaustion of their energy resources. An attacker close to the base station can completely disrupt routing by creating well positioned wormholes that convince nodes multiple hops from the base station that they are only a couple of hops away through the wormhole. G. Hello flood attacks In many routing protocols, nodes broadcast hello messages to announce their presence to their neighbors. A node receiving such a message can assume that the node that sent the message is within its range. An attacker with a high powered antenna can convince every node in the network that it is their neighbor. This section discussed about the wireless sensor networks and sinkhole attack. Rest of the paper is organized as follows: Section 2 provides the review of literature about the Detection of Sinkhole attack using various other approaches. Section 3 explains the proposed methodology. Section 4 discusses the detection of sinkhole attacks in WSNs techniques. Section 5 discusses the experiments conducted and the results. Section 6 concludes the work with future scope. 2. RELATED WORKS Fabrice Le Fessant, et al. [1] focuses on the (1) understanding the impact of selective forwarding attacks on tree-based routing topologies in wireless sensor networks (WSNs), and (2) investigating cryptography-based strategies to limit network degradation caused by sinkhole attacks. The main motivation of the research stems from the following observations. 315 International Journal of Pure and Applied Mathematics Special Issue First, WSN protocols that construct a fixed routing topology may be significantly affected by malicious attacks. Second, considering networks deployed in a difficult to access geographical region, building up resilience against such attacks rather than detection is expected to be more beneficial. Thus first provide a simulation study on the impact of malicious attacks based on a diverse set of parameters, such as the network scale and the position and number of malicious nodes. Based on this study, the authors propose a single but very representative metric for describing this impact. Second, present the novel design and evaluation of two simple and resilient topology-based reconfiguration protocols that broadcast cryptographic values. Edith C.H. Ngai, et al. [2] presents a novel algorithm for detecting the intruder in a sinkhole attack.