TRAP BASED ANOMALY DETECTION MECHANISM FOR WIRELESS SENSOR NETWORK
DOI:
https://doi.org/10.11113/aej.v14.20997Keywords:
Security; Integrity; Attacker; type of attack; IDS.Abstract
A Wireless Sensor Network (WSN) comprises compact, resource-limited devices strategically placed for data collection and transmission, adapting seamlessly across diverse sectors and managing sensitive information. Security is pivotal in these applications, where compromised sensor nodes swiftly jeopardize network integrity, especially without robust security measures. Strategies addressing node compromise center on detecting false data from compromised nodes but often lack precision in tracing the exact source, hindering effective compromised node detection. This paper introduces an inventive anomaly-detection mechanism rooted in trap-based strategies, aiming to prevent sensor node compromise, ensure secure data aggregation, and sustain energy efficiency in WSNs. The trap system integrates deceptive nodes strategically to entice potential attackers, gathering essential attacker details and promptly alerting other network nodes. Consequently, the network excels in identifying attackers and thwarting node compromise, enhancing energy efficiency, network longevity, success rates, and data transmission. Additionally, this approach provides early warning mechanisms for swift attacker detection and attack-type identification, addressing vulnerabilities effectively. By deploying traps proactively, this innovative mechanism not only safeguards against compromises but also fortifies the network's resilience and performance. This proactive strategy aligns with energy efficiency goals in WSNs, elevating the network's security significantly while advancing efficiency across sensitive data domains in sensor network infrastructure.
References
F. S. Cohen, J. C. De Oliveira, and E. Taslidere.2006., “Locating hot nodes and data routing for efficient decision fusion in sensor networks,” Ad Hoc Networks, 4(3): 416–430, doi: 10.1016/j.adhoc.2004.11.001.
D. P. Mishra and R. Kumar, 2015.,“A Vision of Hybrid Security Framework for Wireless Sensor Network Engineering,” Indian Journal of applied Research, 167(1): 2249–555.
R. Di Pietro, L. V. Mancini, and S. Jajodia,2003., “Providing secrecy in key management protocols for large wireless sensors networks,” Ad Hoc Networks, 1(4): 455–468, doi: 10.1016/S1570-8705(03)00046-5.
P. Sharma and P. Bhadana,2010., “An Effective Approach for Providing Anonymity in Wireless Sensor Network: Detecting Attacks and Security Measures,” International Journal of Computer Science Engineering, 02(05): 1830–1835.
M. Bohio and A. Miri,2004., “Efficient identity-based security schemes for ad hoc network routing protocols,” Ad Hoc Networks, 2(3): 309–317, doi: 10.1016/j.adhoc.2004.03.011.
H. Qu,2017., “An Adaptive Intrusion Detection Method for Wireless Sensor Networks,” International Journal of Advanced Computer Science and Applications, 8(11): 27–36.
K. Akkaya, M. Younis, and M. Bangad,2005 “Sink repositioning for enhanced performance in wireless sensor networks,” Computer Networks, 49(4):512-534, doi: 10.1016/j.comnet.2005.01.014.
S. M. Mohamed, H. S. Hamza, and I. A. Saroit,2017., “Coverage in mobile wireless sensor networks (M-WSN): A survey,” Computer Communication., 110:133–150, doi: 10.1016/j.comcom.2017.06.010.
S. Shamsh,2013., “Roaming Honeypots along with IDS in Mobile Ad-Hoc Networks,” International Journal of Computer Applications, 69(23): 14–21.
N. Marchang and R. Datta,2008., “Collaborative techniques for intrusion detection in mobile ad-hoc networks,” Ad Hoc Networks, 6: 508–523, doi: 10.1016/j.adhoc.2007.04.003.
[11] Y. C. Hu, D. B. Johnson, and A. Perrig,2003., “SEAD: Secure efficient distance vector routing for mobile wireless ad-hoc networks,” Ad Hoc Networks, 1(1):175–192, doi: 10.1016/S1570-8705(03)00019-2.
Y. Y. Li and L. E. Parker,2008, “Intruder detection using a wireless sensor network with an intelligent mobile robot response,” Conference Proceedings - IEEE Southeastcon, 37–42, doi: 10.1109/SECON.2008.4494250.
Y. Maleh, A. Ezzati, Y. Qasmaoui, and M. Mbida, 2015, “A global hybrid intrusion detection system for Wireless Sensor Networks,” Procedia Computer Science., 52(1):1047–1052, doi: 10.1016/j.procs.2015.05.108.
S. Shakkottai, R. Srikant, and N. B. Shroff,2015 “Unreliable sensor grids: Coverage, connectivity and diameter,” Ad Hoc Networks, 3(6):702–716, doi: 10.1016/j.adhoc.2004.02.001.
T. A. Zia and A. Y. Zoma Zia, Tanveer & Zomaya, 2011, "A Lightweight Security Framework for Wireless Sensor Networks," Journal of Wireless Mobile Networks, Ubiquitous Computing and Dependable Applications., 2(3): 53–73.
R. K. Ghosh, V. Garg, M. S. Meitei, S. Raman, A. Kumar, and N. Tewari,2006, “Dense cluster gateway based routing protocol for multi-hop mobile ad hoc networks,” Ad Hoc Networks, 4(2):168–185, doi: 10.1016/j.adhoc.2004.04.011.
Y. Yi, M. Gerla, and K. Obraczka,2004, “Scalable team multicast in wireless ad hoc networks exploiting coordinated motion,” Ad Hoc Networks, 2(2):171–184, doi: 10.1016/S1570-8705(03)00053-2.
D. P. Mishra and R. Kumar, 2019, “Hybrid Sink Repositioning Mechanism For Wireless Sensor Network,” International Journal of Research in Advent Technology., 7(3): 1442–1447.
C. Madhusudhanarao,2018, “Flow Sampling for Network Intrusion Detection – An Acceptance Sampling Approach,” International Journal of Applied Engineering Research, 13(13):11030–11033.
M. Li, H. Zhu, and I. Chlamtac,2006, “End-to-end QoS framework for heterogeneous wired-cum-wireless networks,”, Wireless Networks, 12(4): 439–450, doi: 10.1007/s11276-006-6544-z.
