Improved IDR Response System for Sensor Network
DOI:
https://doi.org/10.13052/jwe1540-9589.2013Keywords:
WSN, EIDR, CAO, MODE, IRA, IDSAbstract
Wireless sensor network (WSN) is highly sophisticated than ad hoc wireless network. Ad hoc wireless network is mostly affected by different resources such as high processing energy, storage capabilities and battery backup and etc. Due to the open nature, poor infrastructure, quick deployment practices, and the conflict environments, make them susceptible to a wide range of attacks. Recently, the network attack affects the performance of networks such as network lifetime, throughput, delay, energy consumption, and packet loss. The conventional security mechanisms like intrusion detection system (IDS) of network security are not enough for these networks. In this thesis, we introduce an enhanced intrusion detection and response (EIDR) system using two tire processes. The first contribution of proposed EIDR system is optimal cluster formation and performed by the chaotic ant optimization (CAO) algorithm. The second contribution is to calculate the trust value of each sensor node using the multi objective differential evolution (MODE) algorithm. The computed trust value is used to design the intrusion response action (IRA) system, which offers additional functions and exhibit multiple characteristics of response to mitigate intrusion impacts. The simulation results display that the proposed EIDR system has a better detection rate and false positive rate without affecting network performance.
Downloads
References
A. Bleda, F. Fernandez-Luque, A. Rosa, J. Zapata and R. Maestre, "Smart Sensory Furniture Based on WSN for Ambient Assisted Living", IEEE Sensors Journal, vol. 17, no. 17, pp. 5626-5636, 2017.
J. Wu, K. Ota, M. Dong and C. Li, "A Hierarchical Security Framework for Defending Against Sophisticated Attacks on Wireless Sensor Networks in Smart Cities", IEEE Access, vol. 4, pp. 416-424, 2016.
S. Jokhio, I. Jokhio and A. Kemp, "Light-weight framework for security-sensitive wireless sensor networks applications", IET Wireless Sensor Systems, vol. 3, no. 4, pp. 298-306, 2013.
F. Valeur, G. Vigna, C. Kruegel and R. Kemmerer, "Comprehensive approach to intrusion detection alert correlation", IEEE Transactions on Dependable and Secure Computing, vol. 1, no. 3, pp. 146-169, 2004.
A. Mishra, K. Nadkarni and A. Patcha, "Intrusion detection in wireless ad hoc networks", IEEE Wireless Communications, vol. 11, no. 1, pp. 48-60, 2004.
N. Ye, Q. Chen and C. Borror, "EWMA Forecast of Normal System Activity for Computer Intrusion Detection", IEEE Transactions on Reliability, vol. 53, no. 4, pp. 557-566, 2004.
R. Erbacher, K. Walker and D. Frincke, "Intrusion and misuse detection in large-scale systems", IEEE Computer Graphics and Applications, vol. 22, no. 1, pp. 38-47, 2002.
B. Hoyle, M. Rau, K. Paech, C. Bonnett, S. Seitz and J. Weller, "Anomaly detection for machine learning redshifts applied to SDSS galaxies", Monthly Notices of the Royal Astronomical Society, vol. 452, no. 4, pp. 4183-4194, 2015.
B. Sun, L. Osborne, Y. Xiao and S. Guizani, "Intrusion detection techniques in mobile ad hoc and wireless sensor networks", IEEE Wireless Communications, vol. 14, no. 5, pp. 56-63, 2007.
Yun Wang, Xiaodong Wang, Bin Xie, Demin Wang and D. Agrawal, "Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks", IEEE Transactions on Mobile Computing, vol. 7, no. 6, pp. 698-711, 2008.
S. Shin, T. Kwon, G. Jo, Y. Park and H. Rhy, "An Experimental Study of Hierarchical Intrusion Detection for Wireless Industrial Sensor Networks", IEEE Transactions on Industrial Informatics, vol. 6, no. 4, pp. 744-757, 2010.
S. Bu, F. Yu, X. Liu and H. Tang, "Structural Results for Combined Continuous User Authentication and Intrusion Detection in High Security Mobile Ad-Hoc Networks", IEEE Transactions on Wireless Communications, vol. 10, no. 9, pp. 3064-3073, 2011.
F. Bao, I. Chen, M. Chang and J. Cho, "Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection", IEEE Transactions on Network and Service Management, vol. 9, no. 2, pp. 169-183, 2012.
M. Wei and K. Kim, "Intrusion detection scheme using traffic prediction for wireless industrial networks", Journal of Communications and Networks, vol. 14, no. 3, pp. 310-318, 2012.
J. Chen, J. Li and T. Lai, "Energy-Efficient Intrusion Detection with a Barrier of Probabilistic Sensors: Global and Local", IEEE Transactions on Wireless Communications, vol. 12, no. 9, pp. 4742-4755, 2013.
A. Abduvaliyev, A. Pathan, Jianying Zhou, R. Roman and Wai-Choong Wong, "On the Vital Areas of Intrusion Detection Systems in Wireless Sensor Networks", IEEE Communications Surveys & Tutorials, vol. 15, no. 3, pp. 1223-1237, 2013.
B. Sun, X. Shan, K. Wu and Y. Xiao, "Anomaly Detection Based Secure In-Network Aggregation for Wireless Sensor Networks", IEEE Systems Journal, vol. 7, no. 1, pp. 13-25, 2013.
V. Matyas and J. Kur, "Conflicts between Intrusion Detection and Privacy Mechanisms for Wireless Sensor Networks", IEEE Security & Privacy, vol. 11, no. 5, pp. 73-76, 2013.
G. Han, J. Rodrigues, J. Jiang, L. Shu and W. Shen, "IDSEP: a novel intrusion detection scheme based on energy prediction in cluster-based wireless sensor networks", IET Information Security, vol. 7, no. 2, pp. 97-105, 2013.
H. Moosavi and F. Bui, "A Game-Theoretic Framework for Robust Optimal Intrusion Detection in Wireless Sensor Networks", IEEE Transactions on Information Forensics and Security, vol. 9, no. 9, pp. 1367-1379, 2014.
G. Han, X. Li, J. Jiang, L. Shu and J. Lloret, "Intrusion Detection Algorithm Based on Neighbor Information Against Sinkhole Attack in Wireless Sensor Networks", The Computer Journal, vol. 58, no. 6, pp. 1280-1292, 2014.
K. Lin, T. Xu, J. Song, Y. Qian and Y. Sun, "Node Scheduling for All-Directional Intrusion Detection in SDR-Based 3D WSNs", IEEE Sensors Journal, vol. 16, no. 20, pp. 7332-7341, 2016.
C. Pintea, P. Pop and I. Zelina, "Denial jamming attacks on wireless sensor network using sensitive agents", Logic Journal of IGPL, p. jzv046, 2015.
K. Huang, Q. Zhang, C. Zhou, N. Xiong and Y. Qin, "An Efficient Intrusion Detection Approach for Visual Sensor Networks Based on Traffic Pattern Learning", IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 10, pp. 2704-2713, 2017.
Z. Zhang, H. Zhu, S. Luo, Y. Xin and X. Liu, "Intrusion Detection Based on State Context and Hierarchical Trust in Wireless Sensor Networks", IEEE Access, vol. 5, pp. 12088-12102, 2017.
K. Mrugala, N. Tuptuk and S. Hailes, "Evolving attackers against wireless sensor networks using genetic programming", IET Wireless Sensor Systems, vol. 7, no. 4, pp. 113-122, 2017.
H. Sedjelmaci, S. Senouci and N. Ansari, "Intrusion Detection and Ejection Framework Against Lethal Attacks in UAV-Aided Networks: A Bayesian Game-Theoretic Methodology", IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 5, pp. 1143-1153, 2017.
Q. Guo, X. Li, G. Xu and Z. Feng, "MP-MID: Multi-Protocol Oriented Middleware-level Intrusion Detection method for wireless sensor networks", Future Generation Computer Systems, vol. 70, pp. 42-47, 2017.
D. Santoro, G. Escudero-Andreu, K. Kyriakopoulos, F. Aparicio-Navarro, D. Parish and M. Vadursi, "A hybrid intrusion detection system for virtual jamming attacks on wireless networks", Measurement, vol. 109, pp. 79-87, 2017.
N. Alsaedi, F. Hashim, A. Sali and F. Rokhani, "Detecting sybil attacks in clustered wireless sensor networks based on energy trust system (ETS)", Computer Communications, vol. 110, pp. 75-82, 2017.
X. Jin, J. Liang, W. Tong, L. Lu and Z. Li, "Multi-agent trust-based intrusion detection scheme for wireless sensor networks", Computers & Electrical Engineering, vol. 59, pp. 262-273, 2017.
D. Deif and Y. Gadallah, "An Ant Colony Optimization Approach for the Deployment of Reliable Wireless Sensor Networks", IEEE Access, vol. 5, pp. 10744-10756, 2017.
H. Harno and I. Petersen, "Synthesis of Linear Coherent Quantum Control Systems Using A Differential Evolution Algorithm", IEEE Transactions on Automatic Control, vol. 60, no. 3, pp. 799-805, 2015.