Sinkhole Detection in IOT using Elliptic Curve Digital Signature
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Abstract
A variety of smart applications, including homes, transportation, health, and robots in industries, are starting to gain interest due to the fast expansion of Internet of Things (IoT). Smart devices are made up of sensors and actuators that actively involved in monitoring, prediction, security, and information sharing in the IoT ecosystem. These state-of-the-art (SOTA) technologies enable people to monitor and manage their unified milieu in real-time. IoT devices are nevertheless regularly used in hostile situations, where attackers try to grab and penetrate them to take over the entire network. Due to the possibility of selective forwarding, sinkhole, blackhole, and wormhole attacks on IoT networks is a serious security risk. This research offers an effective method using a digital signature to detect and mitigate sinkhole attacks on IoT networks to resolve this problem. By doing a thorough security study of this suggested system, it shows how safe it is and how resistant it is to secure sinkhole attack detection. In this study, elliptic curve digital signature algorithm is used along with the node ranker to detect the sinkhole attack in IoT environment. According to the performance analysis and experimental findings compared to other research, the suggested system offers good detection accuracy and greatly lowers the overhead associated with computing, communication, and storage.
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References
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