Total views : 204
Sinkhole Attack in Wireless Sensor Networks-Performance Analysis and Detection Methods
Objectives: Wireless sensor networks are used, especially in military, tracking and monitoring applications. Security systems play an important role as the wireless nature is susceptible to attacks. The main idea is to analyse the performance of the network when subjected to sinkhole attack for various scenarios. Methods/Statistical Analysis: Limited energy, computational capacity and storage are some of the constraints on sensor networks which make it to analyze in a different way compared to adhoc networks. In this paper, we discuss the various attacks and attributes which are used to detect the attacks and present a simulation on the effect of sinkhole attack based on various set of parameters. The performance of the system is analyzed when the network is being subjected to sinkhole attack considering the scenarios of varying network size, number of compromised node, intruder power and the location of the sinkhole attack. The available detection methods of the sinkhole attack are tabulated. Findings: Parameters such as average energy consumption, throughput and packet delivery ratio are analyzed. It is seen that the network performance is degraded by the implementation of the attack and there is a decrease in parameters analyzed when subjected to various scenarios. Application/ Improvement: The variation of the parameters in the attack scenarios will be useful in formulating a detection algorithm. The network can be analysed for different scenarios and more number of parameters.
Attack, Packet Delivery Ratio, Performance Analysis, Sensor Network, Sinkhole, Throughput.
- Akyildiz IF, Su W, Sankarasubramaniam E, Cayirci C. Wireless Sensor Networks: A Survey, Computer Networks, Elsevier. 2002; 38(4):394−422.
- Murthy CSR, Manoj RS. Ad Hoc Wireless Networks: Architectures and Protocols by C. Siva Ram Murthy, Prentice Hall, 2004.
- Ye F, Chen A, Lu S, Zhang L. A Scalable Solution to Minimum Cost Forwarding in Large Sensor Networks. In: Conference on Computer Communications and Networks, Arizona, USA, Scottsdale, AZ. 2001; p. 304−09.
- Cetintemel U, Flinders A, Sun Y. Power-Efficient Data Dissemination in Wireless Sensor Networks, In: ACM MobiDE. San Diego, CA, USA. 2003; p. 1−8. Crossref
- Sen JA. Survey on Wireless Sensor Network Security, International Journal of Communication Networks and Information Security (IJCNIS). 2009; 1(3):55−78.
- Xing K, Srinivasan SSR, Rivera M, Li J, Cheng C. Attacks and Countermeasures in Sensor Networks: A Survey Network. Security Springer, 2005, p. 251−72.
- Joseph C, Kishoreraja PC, Baskar R, Reji M. Performance Evaluation of MANETS under Black Hole Attack for Different Network Scenarios, Indian Journal of Science and Technology. 2015; 8(25):1−10. Crossref
- Reji M, Raja PCK, Joseph C, Baskar R. Performance Metrics of Wormhole Detection using Path Tracing Algorithm, Indian Journal of Science and Technology., 2015; 8(17):1−9. Crossref
- Fessent FL, Ppadimitriou A, Viana AC, Sengul C, Palomar P. A Sinkhole Resilient Protocol for Wireless Sensor Networks: Performance and Security Analysis, Computer Communications. 2012; 35(2):234−48.
- Tumrongwittayapak T, Varakulsiripunth R. Detecting Sinkhole Attacks in Wireless Sensor Networks ICROS-SICE International Joint Conference, Fukuoka International Congress Center, Japan; 2009. p. 1966−71.
- Edith CH, Ngai N, Liu JB, Michael R, Lyu L. An Efficient Intruder Detection Algorithm Against Sinkhole Attacks in Wireless Sensor Networks, Computer Communications. 2007; 30(11-12):2353–64. Crossref
- Dallas D, Leckie C, Ramamohanarao K. Hop-Count Monitoring: Detecting Sinkhole Attacks in Wireless Sensor Networks. 15th IEEE International Conference on Networks, ICON Adelaide, SA; 2007. p. 176−81.
- Sheela D, Kumar N, Mahadevan CG. A Non Cryptographic Method of Sinkhole Attack Detection in Wireless Sensor Networks. IEEE-International Conference on Recent Trends in Information Technology, ICRTIT, Chennai, Tamil Nadu; 2011. p. 527−32.
- Sharmila S, Umamaheswari G. Detection of Sinkhole Attack in Wireless Sensor Networks using Message Digest Algorithms. International Conference on Process Automation, Control and Computing (PACC) Coimbatore; 2011. p. 1−6.
- Roy S, Singh S, Choudry S, Debnath N. Countering Sinkhole and Blackhole Attacks on Sensor Networksusing Dynamic Trust Management, Proceedings of IEEE Symposium on Computers and Communinication, Marrakech; 2008. p. 537−42.
- Choi B, Cho Kim J, Hong C, Kim J. A Sinkhole Attack Detection Mechanism for LQI Based Mesh Routing in WSN, Proceedings of International Conference on Information and Networking, Chiang Mai; 2009. p. 1−5.
- Villaipando R, Vargas C, Mnoz D. Network Coding for Detection and Defence of Sinkhole Attacks in Wireless Reconfigurable Networks. Proceedings of International Conference on Systems and Network Communications, Cancun; 2008. p. 286−91.
- Krontis I, Giannetsos T, Dimitriou T, Mpasoukos M. Launching a Sinkhole Attack in Wireless Sensor Networks; the Intruder Side. Proceedings of IEEE International Conference on Wireless and Mobile Computing, Avignon; 2008. p. 526−31.
- Shafei H, khonsari A, Drakshi H, Mousavi P . Detection and Mitigation of Sinkhole Attacks in Wireless Sensor Networks, Journal of Computer and System Sciences. 2013; 80(3):644−53. Crossref
- Liu Y, Passino KM, Intelligence S. Literature Overview, Department of Electrical Engineering. The Ohio State University, 2000.
- Sreelaja NK, Pai GAV, Swarm S. Intelligence Based Approach for Sinkhole Attack Detection in Wireless Sensor Networks, Applied Soft Computing. 2014: 19:68−79. Crossref
- Krontis I, Giannetsos T, Dimitriou T. LIDeA: a Distributed Lightweight Intrusion Detection Architecture for Sensor Networks. Proceedings of ACM Secure Communications, NY; 2008.
- Chen C, Song M, Hsieh G. Intrusion Detection of Sinkhole Attacks In Large-scale Wireless Sensor Networks. IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS), Beijing, China; 2010. p. 711−16. PMCid:PMC3398139.
- Sinkhole S. Attack Detection Based on Redundancy Mechanism in Wireless Sensor Networks, Fang-Jiao Zhanga, Li-Dong Zhaia, Jin-Cui Yangb, Xiang Cuic, Procedia Computer Science. 2014; 13(31):711–20.
- Shamshirband S, Amini A, Anuar NB, Kiah MLM, Wah Y. Steven Furnell D-FICCA: A Density-Based Fuzzy Imperialist Competitive Clustering Algorithm for Intrusion Detection in Wireless Sensor Networks, Measurement. 2014; 55:212–22. Crossref
- Kishore Raja PC, Sathishkumar M, Christeena Joseph, Reji M, Radhika Baskar. Real Time Experimental Analysis of Mobile Ad-Hoc Traffic in Indoor and Outdoor Environment, International Journal of Engineering and Technology. 2015 Jun-Jul; 7(3):922−28.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.