analysis of spatial and transmission features for efficient black hole attack detection in wsn using attacker detection metrics

Abstract

The growth of communication and information technology has enabled newlinethe access of different network services independent of the user location. Due to newlinethe restriction in physical characteristics of sensor nodes, they involve in newlinecooperative transmission. The sensor nodes access any network service through newlinethe support of other intermediate nodes. The presence of malicious node in the newlinenetwork or route, introduces variety of threats. Black whole attack is the most newlinedangerous one which allow the malicious node to perform different threats. newlineHowever, there exist different approaches in mitigating the black hole attack, but newlinesuffer with various QoS performance. To improve the performance, first, an newlineefficient Attacker Detection Metrics (ADM) based black hole attack detection newlinescheme is proposed. The method discovers the routes to reach destination and newlineextract sequence number of the packets. According to average sequence value, newlinesubsets of routes are identified with higher sequence value. For the selected newlinenodes, a dummy packet has been sent and based on the acknowledgement, newlinemalicious nodes are detected and updated state table has been flood to mitigate newlinethe attack. Proposed ADM approach improves the security performance. Further newlineto improve the performance in black hole attack detection, a spatial transmission newlineanalysis model (STABD) is proposed. The method uses route discovery newlineprocedure to find the routes and number of transmission performed, location, newlineenergy of nodes in the route. Features extracted are used to perform spatial trust newlineanalysis to measure distance covered and average hop count to measure the newlinevalue of Spatial Trust Measure (STM). Similarly, the method performs transmission newlinetrust analysis (TTA) to measure Trusted Energy Support (TES) and Trusted newlineHandling Support (THS) to compute Trusted Transmission Factor (TTF). Using the newlinevalue of STM and TTF the method compute the value of trust weight TW, based newlineon which black hole attack detection has been performed. The proposed STABD newlinealgorithm produces h