Abstract
Wireless sensor network is defined as homogeneous or heterogeneous system containing large number of sensors namely called as nodes used to monitor different environments in cooperatives. WSN is composed of sensor nodes (SN), base stations (BS) and cluster head (CH). The popularity of wireless sensor network has been increased day by day exponentially due to its wide range of application. The applications of wireless sensor networks are air traffic control, healthcare systems, home services, military services, industrial & building automations, network communications, VAN etc. The advantage of WSN is that it is very easy to install in critical regions where normal network cannot be set. Thus the wide range of applications attracts attacker. To secure from different types of attacks mainly intruder, intrusion detection system based on dynamic state context and hierarchical trust in WSNs (IDSHT) is proposed. The trust evaluation is carried out in hierarchical way. The trust of sensor nodes is evaluated by cluster head (CH) whereas trust of cluster head is evaluated by neighbor cluster head or base stations. Hence the content trust, honest trust and interactive trust is put forward by combining direct evaluation and feedback based evaluation in the fixed hop range. In this way the complexity of trust management is carried in hierarchical manner and trust evaluation overhead is minimized. This proposed work addresses the security issues of wireless sensor network. A more prominent intrusion detection system based on context level and trust level is introduced. This mechanism achieves more than 90% accuracy in detection of routing attack and sinkhole attack. The architecture suggested in this paper is used to develop two level of trust model. Accuracy of 90% and 95% is expected in intrusion detection and context text detection respectively.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhang Z, Zhu H, Luo S, Xin Y, Liu X (2017) Intrusion detection based on state context and hierarchical trust in wireless sensor networks. IEEE Trans Content Min
Benisha RB, Raja Ratna Dr S (2018) Prevention of cyber attacks in control systems: a review. In: Proceedings of the 2nd international conference on trends in electronics and informatics (ICOEI 2018)
Ntalampiras S (2014) Detection of integrity attacks in cyber-physical critical infrastructures using ensemble modelling. In: IEEE transactions on industrial informatics, vol 11
Sadi Y, Ergen SC, Park P (2014) Minimum energy data transmission for wireless networked control systems. IEEE Trans Wirel Commun 13(4):2163–2175
He D, Chen C (2012) A distributed trust evaluation model and its application scenarios for medical sensor networks. In: IEEE transactions on information technology in biomedicine, vol 16, no 6
Boukerche A, Li X, El-Khatib K (2007) Trust-based security for wireless ad hoc and sensor networks. Comput Commun 30:2413–2427
Maddar H, Kammoun W, Youssef H (2017) Trust intrusion detection system based on location for wireless sensor network. Springer International Publishing AG
Liu K, Abu-Ghazaleh N, Kang K-D (2007) Location verification and trust management for resilient geographic routing. Parallel Distrib Comput 67(2):215–228
He T, Stankovic JA, Lu C, Abdelzaher T (2003) SPEED: a stateless protocol for real-time communication in sensor networks. In: Proceedings of the 23rd international conference ondistributed computing systems (ICDCS’03), Washington, DC, USA, pp 46–55
Zhou M-Z, Zhang Y, Wang J, Zhao S-Y (2009) A reputation model based on behavior trust in wireless sensor networks. In: Eighth IEEE international conference on scalable computing and communications
Jadidoleslamy H (2011) A hierarchical intrusion detection architecturer for wireless sensor networks. Int J Netw Secur Its Appl (IJNSA) 3(5)
Bao F, Chen I, Chang M, Cho J (2012) Hierarchical trust management for wireless sensor networks and its applications to trust-based routing and intrusion detection. IEEE Trans Netw Serv Manage 9(2):169–183
Li X, Zhou F, Du J (2013) LDTS: a lightweight and dependable trust system for clustered wireless sensor networks. IEEE Trans Inf Forensics Secur 8(6):924–935
Shaikh RA, Jameel H, d’Auriol BJ, Lee H, Lee S, Song Y (2009) Group-based trust management scheme for clustered wireless sensor networks. IEEE Trans Parallel Distrib Syst 20(11):1698–1712
Butun I, Morgera SD, Sankar R (2014) A survey of intrusion detection systems in wireless sensor networks. IEEE Commun Surv Tutor 16(1):234–241
Heinzelman WR, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor netw orks. IEEE Trans Wirel Commun 1(4):660–670
Ye M, Li C, Chen G, Wu J (2005) An energy efficient clustering scheme in wireless sensor networks. In: PCCC 2005, 24th IEEE international performance, computing, and communications conference
Hao F, Min G, Lin M, Luo C, Yang L (2014) MobiFuzzyTrust: an efficient fuzzy trust inference mechanism in mobile social networks. IEEE Trans Parallel Distrib Syst 25(11):2944–2955
Kalnoor G, Agarkhed J (2018) Intrusion threats and security solutions in wireless sensor networks. Int Robot Autom J
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Kagade, R.B., Santhosh, J. (2021). State Context and Hierarchical Trust Management in WSN for Intrusion Detection. In: Pawar, P.M., Balasubramaniam, R., Ronge, B.P., Salunkhe, S.B., Vibhute, A.S., Melinamath, B. (eds) Techno-Societal 2020. Springer, Cham. https://doi.org/10.1007/978-3-030-69921-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-69921-5_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-69920-8
Online ISBN: 978-3-030-69921-5
eBook Packages: EngineeringEngineering (R0)