The International Arab Journal of Information Technology (IAJIT)


FBMT: Fuzzy Based Merkle Technique for

Wireless sensor networks are prone to many vulnerabilities because of its unattended environment policy. Intrusion is one of the serious issue in wireless networks, since wireless networks are resource constrained and devising a security mechanism to counter intrusion is a challenging task. This paper focuses on building light-weight Intrusion Detection System to counter the routing attack, by identifying the malicious nodes at the earliest point. The proposed scheme namely Fuzzy Based Merkle Technique applies fuzzy logic to identify the malicious nodes and builds a light-weight Intrusion detection system and adapts Merkle tree approach for building the network. The proposed scheme is efficient in identifying the malicious nodes with minimum energy consumption and less communication overhead than the existing Merkle technique. Network Simulator 2 is used to simulate the Intrusion Detection System (IDS) and the results are verified.

[1] Baadache A. and Belmehdi A., “Fighting Against Packet Dropping Misbehavior in Multi-Hop Wireless Ad Hoc Networks,” Journal of Network and Computer Applications, vol. 35, no. 3, pp. 1130-1139, 2012.

[2] Bhatiya A., Tilwankar A., Lambhate D., and Kumar K., “Detection and Prevention of Sink Hole Attack in AODV Protocol for Wireless Sensor Network,” International Research Journal of Engineering and Technology, vol. 4, no. 5, pp. 2192- 2201, 2017.

[3] Chandran K., Shanmugasudaram V., and Subramani K., “Designing a Fuzzy-Logic Based Trust and Reputation Model for Secure Resource Allocation in Cloud Computing,” The 1112 The International Arab Journal of Information Technology, Vol. 16, No. 6, November 2019 International Arab Journal of Information Technology, vol. 13, no. 1, pp. 30-37, 2016.

[4] Denning D., “An Intrusion-Detection Model,” IEEE Transactions on Software Engineering, vol. 13, no. 2, pp. 222-232, 1987.

[5] Goztepe K., “Designing a Fuzzy Rule Based Expert System for Cyber Security,” International Journal of Information Security Science, vol. 1, no. 1, pp. 13-19, 2012.

[6] Gronkvist J., Hansson A., and Skold M., “Evaluation of a Specification-Based Intrusion Detection System for AODV,” in Proceedings of 6th annual Mediterranean Ad Hoc Networking Workshop, Corfu, pp. 121-128, 2007.

[7] Javanmardi S., Barati A., Dastgheib S., and Attarzadeh I., “A Novel Approach for Faulty Node Detection with the aid of Fuzzy Theory and Majority Voting in Wireless Sensor Networks,” International Journal of Advanced Smart Sensor Network Systems, vol. 2, no. 4, 2012.

[8] Liao H., Lin C., Lin Y., and Tung K., “Intrusion Detection System: A Comprehensive Review,” Journal of Network and Computer Applications, vol. 36, no. 1, pp. 16-24, 2013.

[9] Mathew A. and Terence S., “A Survey on Various Detection Techniques of Sinkhole Attacks in WSN,” in Proceedings of the IEEE International Conference on Communication and Signal Processing, Chennai, pp. 1115-1119, 2017.

[10] Merkle R., “A Digital Signature Based on a Conventional Encryption Function,” in Proceedings of Advances in Cryptology- CRYPTO’87, Santa Barbara, pp. 369-378, 1987.

[11] Raja S. and Ramaiah S., “Performance Comparison of Neuro-Fuzzy Cloud Intrusion Detection Systems,” The International Arab Journal of Information Technology, vol. 13, no. 1A, pp. 142-149, 2016.

[12] Ruschitzka K. and Levitt K., “Execution Monitoring of Security-Critical Programs in Distributed Systems: A Specification-based Approach,” in Proceedings of IEEE Symposium on Security and Privacy, Oakland, pp. 175-187, 1997.

[13] Santhi G. and Sowmiya R., “A Survey on Various Attacks and Countermeasures in Wireless Sensor Networks,” International Journal of Computer Applications, vol. 159, no. 7, pp. 7-11, 2017.

[14] Sharma K. and Vairamuthu S., “Enhancing The Security Through the Usage of Merkle Tree and Timestamp in Peer to Peer Messaging,” International Journal of Pure and Applied Mathematics, vol. 119, no. 7, pp. 13-20, 2018.

[15] Siddiqui S., Khan P., and Khan M., “Fuzzy Logic Based Intruder Detection System in Mobile Ad hoc Network,” Bharati Vidyapeeth’s Institute of Computer Applications and Management International Journal of Information Technology, vol. 6, no. 2, pp. 767-773, 2014.

[16] Singh J., Kaur L., and Gupta S., “A Cross-Layer Based Intrusion Detection Technique for Wireless Networks,” The International Arab Journal of Information Technology, vol. 9, no. 3, pp. 201-207, 2012.

[17] Sundararajan R. and Arumugam U., “Intrusion Detection Algorithm for Mitigating Sinkhole Attack on LEACH Protocol in Wireless Sensor Networks,” Journal of Sensors, vol. 2015, 2015.

[18] Tseng C., Balasubramanyan P., Ko C., Limprasittiporn R., Rowe J., and Levitt K., “A Specification-based Intrusion Detection System for AODV,” in Proceedings of the 1st ACM workshop on Security of Ad hoc and Sensor Networks, Washington, pp. 125-134, 2003.

[19] Yu Y., Li K., Zhou W., and Li P., “Trust Mechanisms in Wireless Sensor Networks: Attack Analysis and Countermeasures,” Journal of Network and Computer Applications, vol. 35, no. 3, pp. 867-880, 2012.

[20] Zadeh L., “Fuzzy Sets,” Information and Control, vol. 8, pp. 338-353, 1965. FBMT: Fuzzy Based Merkle Technique for Detecting and Mitigating Malicious ... 1113 Ranjeeth Kumar Sundararajan started the basic degree in computer science in Jawahar Science College, Neyveli, Tamilnadu, India. He completed his Master degree in computer technology from Coimbatore Institute of Technology, Coimbatore, Tamilnadu, India and a Master degree in computer science and engineering from Pavendar Bharathidasan College of Engineering and Technology, Trichirappalli, Tamilnadu, India. He had completed his Ph.D in the field of Wireless Sensor Networks from SASTRA Deemed University. He has 5.5 years of teaching experience in engineering institutions and participated in several conferences and workshops. He published one research paper in international conference and participated in young IT professional competition conducted by CSI India. He is currently working as an Assistant Professor in the department of Computer Science & Engineering, Srinivasa Ramanujan Centre, SASTRA Deemed University, Kumbaonam, Tamilnadu, India. His research interests are Network Security, Wireless Sensor Networks, Cloud Computing, Internet of Things and Objected Oriented Design. Umamakeswari Arumugam received her Bachelor’s degree in Engineering from A.C.C.E.T., Karaikudi in 1989, Master’s Degree in 1994 from NIT (formerly REC), Trichy and Doctorate from SASTRA University in 2009. She has 25 years of work experience and her research interests are in the area of Computer Vision, Embedded Systems, Wireless Sensor Networks and Software Engineering. She has presented papers in Conferences and published papers in reputed Journals. She has done collaborative projects and also organized international conferences. She is currently working as Dean, School of Computing, SASTRA Deemed University, Thanjavur- 613401, Tamil Nadu, India.