Internet of Things (IoT) is an internet of smart objects where smart objects communicate with each other. IoT objects are deployed in open medium with dynamic topology. Due lack of infrastructure and centralized management, IoT present serious vulnerabilities to security attacks. Therefore, security is an essential prerequisite for the real-world deployment of IoT. In this work, we propose reputation-based RPL protocol where reputation-based mechanism is embedded into RPL protocol to enhance its capabilities against selective forwarding attack. Reputation is calculated by evaluating data forwarding behavior of IoT node. Data forwarding behavior of IoT node is evaluated by the difference between monitored actual packet loss and estimated normal loss. Calculated reputation value is considered in parent selection. Simulation results show that the proposed approach can accurately detect and isolate selective forwarding attack with improving data delivery ratio of the IoT network.
Internet of things (IoT) offers communication between user-to-machine and machine-to-machine. Due to their inherent characteristics of open medium, very dynamic topology, lack of infrastructure and lack of centralized management authority, IoT present serious vulnerabilities to security attacks. The routing protocol for low-power and lossy networks (RPL) does not have an inherent mechanism to detect routing attacks. Popular among these IoT attacks is blackhole attack. An attacker can exploit the routing system of RPL to launch blackhole attack against an IoT network. To secure IoT networks from blackhole attack, trust-integrated RPL protocol (TRPL) is proposed and implemented. The trust system is embedded in the RPL protocol to detect and isolate a blackhole attack while optimizing network performance. The trust is calculated from successful interaction between two nodes. The calculated trust value is considered in parent selection. TRPL demonstrates its superior performance over the standard RPL protocol and existing techniques in the detection and isolation of blackhole attacks.
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