Abstract
The emerging technology of Wireless sensor network is expected to provide Intrusion detection technique for all kind of attacks. This article models and analyzes intrusion detection using flow-based IDS and cross-layered approach. The Critical application needs to replace cryptographic technique with flow-based anomaly detection for secure communication and single layer detection method with multi-layer detection method for efficient attack detection. The proposed detection system has a two-phase approach. In the first phase, flow-based anomaly detection method is used to detect potential anomalies in the network traffic. During second phase cross–layer features are correlated to narrow down the possible attacks. Simulation results clearly show that the proposed detection technique has an excellent performance in terms of detection accuracy, the energy consumption, and the false positive rate will reduce than the layer-based approach and packet-based approach.
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REFERENCES
Fabrizio Angiulli, Luciano Argento, and Angelo Furfaro, Exploiting content spatial distribution to improve detection of intrusions, ACM Trans. Internet Technol., 2018, vol. 18, no. 2, pp. 1802–1825.
Muhammad Fahad Umer and Sher, M.Bi.Y., A two-stage flow-based intrusion detection model for next-generation networks, PloS One, 2018, vol. 13, no. 1, pp. 1–20.
Babber, K. and Randhawa, R., A cross-layer optimization framework for energy efficiency in wireless sensor networks, Wireless Sensor Network, 2017, vol. 9, no. 6, pp. 189–203.
Ganesh Reddy Karri and P. Santhi Thilagam, Reputation-based cross-layer intrusion detection system for wormhole attacks in wireless mesh networks, Secur. Commun. Networks, 2014, vol. 7, pp. 2442–2462.
Joseph, J.F.C., et al., Cross-layer detection of sinking behavior in wireless ad hoc networks using SVM and FDA, IEEE Trans. Defendable Secure Comput., 2011, vol. 8, no. 2, pp. 233–245.
Vuran, M.C., et al., XLP: A cross-layer protocol for efficient communication in wireless sensor networks, IEEE Trans. Mobile Commun., 2010, vol. 9, no. 11, pp. 1578–1591.
Ushaa, G., Rajesh Babub, M., and Saravana Kumar, S., Dynamic anomaly detection using cross layer security in MANET, Comput. Electr. Eng., 2017, vol. 59, pp. 231–241.
Joseph, J.F.C., Amitabha Das, Bu-Sung Lee, and Boon-Chong Seet, CARRADS: Cross layer based adaptive real-time routing attack detection system for MANETS, Comput. Networks, 2010, vol. 54, no. 7, pp. 1126–1141.
Elejla, O.E., et al., Flow-based IDS for ICMPv6-based DDoS attacks detection, Arabian J. Sci. Eng., 2018, vol. 43, no. 12, pp. 7757–7775.
Mansour Sheikhan, et al., Flow-based anomaly detection in high-speed links using modified GSA-optimized neural network, Neural Comput. Appl., 2014, vol. 24, no. 3, pp. 599–611.
Sathya, D., Krishneswari, K., et al., Cross-layer intrusion detection system for wireless sensor networks, J. Sci. Ind. Res., 2016, vol. 75, no. 4, pp. 213–220.
Gandhimathi, L. and Murugaboopathi, G., Cross layer intrusion detection and prevention of multiple attacks in wireless sensor network using mobile agent, International Conference on Communication and Embedded Systems, 2016. https://doi.org/10.1109/ICICES.2016.7518935
Md. Motaharul Islam, et al., Honeypot based cellular cross-layer intrusion detection and response, Int. J. Comput. Sci. Network Secur., 2018, vol. 18, no. 6, pp. 104–111.
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L. Gandhimathi and G. Murugaboopathi declare that they have no conflicts of interest.
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Gandhimathi, L., Murugaboopathi, G. A Novel Hybrid Intrusion Detection Using Flow-Based Anomaly Detection and Cross-Layer Features in Wireless Sensor Network. Aut. Control Comp. Sci. 54, 62–69 (2020). https://doi.org/10.3103/S0146411620010046
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DOI: https://doi.org/10.3103/S0146411620010046