Abstract
Information sensing and data aggregation are vital components for technologies like Machine learning, Big data, IoT, and Cloud computing. Providing security to data sensed in WSNs is critical. The risk of destructive security risks has risen as the resources are limited. Encryption, authentication, and firewalls are the first line of defense but not adequate. Collaborative Intrusion prevention and detection approaches complement security as the second line of defense. This review aims to provide insights into solutions to prevent, detect, and mitigate WSN intrusions. This paper provided an outline of WSN at the beginning of this review paper, and then we elaborated and compared a broad range of intrusion detection methodologies to demonstrate their performance. Finally, we concluded the report with an insightful potential course of study into the state-of-the-art fields that enable researchers in this area to assess their work.
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References
Butun I, Morgera S, Sankar R (2014) A survey of intrusion detection systems in wireless sensor networks. IEEE Commun Surv Tutorials 16(1):266–282. https://doi.org/10.1109/surv.2013.050113.00191
Tervoort T, De Oliveira M, Pieters W, Van Gelder P, Olabarriaga S, Marquering H (2020) Solutions for mitigating cybersecurity risks caused by legacy software in medical devices: a scoping review. IEEE Access 8:84352–84361
Stallings W (1998) Cryptography and network security: principles and practice, 2nd edn. Prentice-Hall
Dahill B, Sanzgiri K, Levine BN, Shields C, Belding-Royer EM (2002) A secure routing protocol for ad hoc networks. In: Proceedings of the IEEE ICNP
Liao HJ, Richard LC, Lin Y, Tung KY (2013) Intrusion detection system: a comprehensive review. J Netw Comput Appl 36(1):16–24
Chandre PR, Mahalle PN, Shinde GR (2018) Machine learning based novel approach for intrusion detection and prevention system: a tool based verification. In: 2018 IEEE global conference on wireless computing and networking (GCWCN), Lonavala, India, 2018, pp 135–140. https://doi.org/10.1109/GCWCN.2018.8668618
AVISPA: Automated validation of internet security protocols and applications (2003) FET Open Project IST-2001-39252. www.avispaproject.org
Otoum S, Kantarci B, Mouftah HT (2019) On the feasibility of deep learning in sensor network intrusion detection. IEEE Netw Lett 1(2):68–71. https://doi.org/10.1109/LNET.2019.2901792
Jianjian D, Yang T, Feiyue Y (2018) A novel intrusion detection system based on IABRBFSVM for wireless sensor networks. Procedia Comput Sci 131:1113–1121. https://doi.org/10.1016/j.procs.2018.04.275
Xie J, Tao Y, Yang F, Pan L, Xu J, Hou Y (2018) Intrusion detection system for hybrid DoS attacks using energy trust in wireless sensor networks. Procedia Comput Sci 131:1188–1195. ISSN 1877-0509
Ghugar U, Pradhan J (2018) NL-IDS: trust based intrusion detection system for network layer in wireless sensor networks. In: 2018 fifth international conference on parallel, distributed and grid computing (PDGC), Solan Himachal Pradesh, India, pp 512–516. https://doi.org/10.1109/PDGC.2018.8745870
Coppolino L, DAntonio S, Garofalo A, Romano L (2013)Applying data mining techniques to intrusion detection in wireless sensor networks. In: 2013 eighth international conference on P2P, parallel, grid, cloud and internet computing, Compiegne, pp 247–254. https://doi.org/10.1109/3PGCIC.2013.43
Huang YA, Fan W, Lee W, Yu PS (2003) Cross-feature analysis for detecting ad-hoc routing anomalies. In: Proceedings of the 23rd IEEE international conference distributed computing systems, Rhode Island, USA
Sezer S, Scott-Hayward S, Chouhan P (2013) Are we ready for SDN? Implementation challenges for software-defined networks. IEEE
Grandison T, Sloman M (2000) A survey of trust in internet applications. Tutorials
Ndiaye M, Hancke GP, Abu-Mahfouz AM. Software defined networking for improved wireless sensor network management: a survey. Sensors 17(5)
Miranda C, Kaddoum G, Bou-Harb E, Garg S, Kaur K (2020) A collaborative security framework for software-defined wireless sensor networks. IEEE Trans Inf Forensics Secur 15:2602–2615
Peng H, Sun Z, Zhao X, Tan S, Sun Z (2018) A detection method for anomaly flow in software defined network. IEEE Access 6:27809–27817. https://doi.org/10.1109/ACCESS.2018.2839684
Cheng BC, Tseng RY (2011) A context adaptive intrusion detection system for MANET. Comput Commun 34(3):310–318
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Sirajuddin, M., Sateesh Kumar, B. (2022). Collaborative Security Schemes for Wireless Sensor Networks. In: Kumar, A., Mozar, S. (eds) ICCCE 2021. Lecture Notes in Electrical Engineering, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-16-7985-8_36
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DOI: https://doi.org/10.1007/978-981-16-7985-8_36
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