Intrusion Detection in Wireless Sensor Networks Based on IPSO-SVM Algorithm
DOI:
https://doi.org/10.13052/jcsm2245-1439.13410Keywords:
PSO algorithm, SVM algorithm, Wireless sensor network, Intrusion detection, DEEC algorithmAbstract
To optimize node energy consumption and improve its security, this paper uses the DEEC algorithm to layer WSN and reduce the probability of channel information collision and uses the weighted probability of cluster head election to optimize node energy expenditure, so that WSN can obtain a longer lifecycle. Improved Particle Swarm Optimization-based Support Vector Machine (IPSO-SVM) algorithm is used for intrusion detection and experimental testing in WSN. The results showed that the IPSO-SVM algorithm exhibited good convergence, with a convergence step size of 5 steps, which converged earlier than the Support Vector Machine Algorithm based on Particle Swarm Optimization (PSO-SVM), which had a convergence step size of 10 steps. The IPSO-SVM algorithm performed best in WSN intrusion detection, with the highest detection rate of 96.20% in Probe attack data detection, which was 0.80% higher than the Support Vector Machine Algorithm based on Genetic Algorithm (GA-SVM). The PSO-SVM algorithm had the lowest detection rate of 95.20%. The IPSO-SVM algorithm had a minimum false positive rate of 1.54% in Dos attack data detection. In terms of average training time, the IPSO-SVM algorithm had a minimum average training time of 323.45 seconds. Compared to the Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm, the Distributed Energy Efficient Clustering (DEEC) algorithm performs better, has less energy consumption, and retains more nodes. The method adopted in this study can make WSN have a longer life cycle and ensure its security.
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DashMeera, PanigrahiTrilochan, SharmaRenu, MM Narayan. Adaptive Parameter Estimation of IIR System-Based WSN Using Multihop Diffusion in International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2020,14(4):30–41.
Han Z, Ding H, Yue K, L Bao, Z Yang. New type NP-CSMA of adaptive multi-priority control WSN protocol analysis. International Journal of Reasoning- based Intelligent Systems, 2021, 13(1):24–31.
Jegan J, Sivakumar D, Selvakumar K. Swarm Based Novel Energy Aware Clustering Algorithm for WSN in Realtime Applications. international journal of computational intelligence theory and practice, 2021,16(2):73–89.
Hebal S, Louail L, Harous S. Latency and Energy Optimization Using MAC-Aware Routing for WSNs. International Journal of Business Data Communications and Networking, 2020, 16(1):19–27.
Xiu-Wu Y U, Hao Y U, Liu Y, RR Xiao. a clustering routing algorithm based on wolf pack algorithm for heterogeneous wireless sensor networks. computer Networks, 2019, 167(6):106994.1–106994.10.
Borkar G M, Patil L H, Dalgade D, A Hutke. A novel clustering approach and adaptive SVM classifier for intrusion detection in WSN: A data mining concept. Sustainable Computing, 2019, 23(Sep.):120–135.
Alghamdi W, Rezvani M, Wu H, Kanhere, Salil S. Routing-Aware and Malicious Node Detection in a Concealed Data Aggregation for WSNs. ACM Transactions on Sensor Networks, 2019, 15(2):18.1–18.20.
Behera T M, Mohapatra S K. A novel scheme for mitigation of energy hole problem in wireless sensor network for military application. international Journal of Communication Systems, 2021, 34(11): e4886.1–e4886.10.
Banerjee A, Das V, Biswas A, S Chattopadhyay, U Biswas. Development of Energy Efficient and Optimized Coverage Area Network Configuration to Achieve Reliable WSN Network Using Meta-Heuristic Approaches. international journal of geotechnical earthquake engineering, 2021, 12(3):1–27.
Amarasimha T, Rao V S. Efficient Energy Conservation and Faulty Node Detection on Machine Learning-Based Wireless Sensor Networks. Journal of Grid and High-Performance Computing, 2021, 13(2):1–20.
Liang J, Xu Z, Xu Y, W Zhou, C Li. Adaptive cooperative routing transmission for energy heterogeneous wireless sensor networks. physical Communication, 2021, 49(Dec.):101460.1–101460.10.
Xu Y, Jiao W, Tian M. Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks. sensors, 2020, 20(21):1–19.
Wei J, Huang H, Kang P D. PSO-DEC-IFSVM Classification Algorithm for Unbalanced Data. Shu Ju Cai Ji Yu Chu Li/Journal of Data Acquisition and Processing, 2019, 34(4):723–735.
Li Q, Fu Q, Zou Y, Xijun Hu. Evaluation of Livable City Based on GIS and PSO-SVM: A Case Study of Hunan Province. international Journal of Pattern Recognition and Artificial Intelligence, 2021, 35(8):2159030.1–2159030.18.
Varela N, Lezama O, Neira H. Information security in WSN applied to smart metering networks based on cryptographic techniques. journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2020, 39(6 Pt. 1):8499–8506.
Kala I, Karthik S, Srihari K. Advanced hybrid secure multipath optimized routing in Internet of Things (IoT)-based WSN. International Journal of Communication Systems, 2021, 34(8):e4782.1–e4782.14.
Bayat M, Atashgah M B, Barari M, MR Aref. Cryptanalysis and Improvement of a User Authentication Scheme for Internet of Things Using Elliptic Curve Cryptography. International Journal of Network Security, 2019, 21(6):897–911.
Neethu P S, Suguna R, Rajan P S. Performance evaluation of SVM-based hand gesture detection and recognition system using distance transform on different data sets for autonomous vehicle moving applications. circuit world, 2022, 48(2):204–214.
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