Graph based event measurement for analyzing distributed anomalies in sensor networks
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Ó Indian Academy of Sciences Sadhana(0123456789().,-volV)F T3](0123456789().,-volV)
Graph based event measurement for analyzing distributed anomalies in sensor networks P SHERUBHA1,* , S P SASIREKHA1, V MANIKANDAN2, K GOWSIC3 and N MOHANASUNDARAM1 1
Department of Computer Science and Engineering, Karpagam Academy of Higher Education, Coimbatore, India 2 Computer Networks, College of Engineering and Computer Science, Lebanese French University, Erbil, Iraq 3 Department of Information Technology, KSR Institute for Engineering and Technology, Tiruchengode, India e-mail: [email protected] MS received 20 April 2020; revised 13 May 2020; accepted 5 July 2020 Abstract. Wireless Sensor Network (WSN) has emerged drastically with numerous practical applications of considerable Engineering importance where privacy and security are of dominant influence. This paves the way for this investigation and present interest in the development of novel and innovative intrusion detection approach. This work anticipated a novel Intrusion detection framework by modeling sensor connectivity with a targeted graph and uses statistical graph properties by modeling intrusion detection. In anticipated graph-based detection, data capturing magnitude is modeled with the Gaussian model, and the corresponding correntropy is estimated by graph matrix with adaptive sensor measurements. Anticipated detection approach is modeled based on the Laplacian Matrix, and closed-form expressions are attained for statistical analysis. At last, temporal network analysis are characterized by evaluating sensor distance among measurement distributions in consecutive time. The results depict that the anticipated detection framework offers superior detection recital than compared to existing frameworks. Keywords. Wireless Sensor Networks; intrusion detection; distributed sensor network; graph connectivity; corr-entropy computation; statistical distance measures.
1. Introduction Wireless Sensor Networks (WSNs) are considered as the integration of communication, control, and computation technologies that are cast-off to manage and monitor infrastructures [1]. Improvements in sensor technologies and communication have offered deployment of massive nodes in WSN, those results in exception growth in the opportunistic implementation of an application to those systems [2]. The tremendous growth in WSNs leads to claims with an acute condition that has raised interest in security crisis [3]. In specific, concentration is towards network-based intrusion detection is distinctive and shows irregular changes in capturing data in nodes [4]. Authentic functionalities like transient variations in vapor detection from the smoke detector and criminal activities like worms and virus injection in power grids are two instances of such intrusions. In recent times, sensor networks are integrated with cyber-physical systems, which play a significant task
*For correspondence
in the advancement and management of economic and social infrastructures [5]. The current advancement in graph
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