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Wireless sensor network security: Real-time detection and prevention of attacks

Publication Type : Conference Paper

Thematic Areas : Wireless Network and Application

Publisher : Proceedings - 4th International Conference on Computational Intelligence and Communication Networks

Source : Proceedings - 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012, Mathura, Uttar Pradesh, 2012, pp. 783-787

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84872011446&partnerID=40&md5=aced2a2a1df692ab6f130b171631a61a

Keywords : Artificial intelligence, Computer crime, Confidential information, Critical issues, Denial of Service, DoS attacks, Energy cost, Execution time, Learning systems, Lower memory requirement, Machine learning techniques, MICAz motes, Network security, Passive information, Random access storage, Real-time detection, Real-world application, Security, Security mechanism, Sensor nodes, Symmetric cryptography, Symmetric keys, Telecommunication networks, tinyos, Wireless sensor network (WSNs), Wireless sensor networks, Wireless sensor node

Campus : Amritapuri

School : School of Engineering

Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)

Department : Wireless Networks and Applications (AWNA)

Year : 2012

Abstract : Security is a critical issue in many real-world applications of wireless sensor networks (WSNs). This research focuses on implementing security mechanisms, against two specific types of attack that occur in a network of MICAz motes. These are 'denial-of-service' (DoS) attacks where unnecessary packets are sent causing services to appear unavailable and thus these services are denied to the legitimate sensor nodes, and 'passive information gathering' attacks where an adversary tries to obtain the confidential information stored in wireless sensor nodes. A machine learning technique named neural network (NN) is used to detect DoS attack conducted by an adversary. We compare and evaluate NN with our new method. The results clearly show an improved performance for our new proposed symmetric-key algorithm compared to NN. Lower encryption computational energy cost (8 μJ vs 16 μJ), lower memory requirements (8896 bytes of ROM and 434 bytes of RAM vs 15848 bytes of ROM and 763 bytes of RAM), and less execution time (0.164835 ms vs 0.6208791 ms) show the significant advantages of using symmetric-key algorithm instead of NN for detecting DoS attack. © 2012 IEEE.

Cite this Research Publication : Dr. Maneesha V. Ramesh, Raj, A. B., and Hemalatha, T., “Wireless sensor network security: Real-time detection and prevention of attacks”, in Proceedings - 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012, Mathura, Uttar Pradesh, 2012, pp. 783-787

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