Robust link-assessment-based approach for detection and isolation of blackhole attacker in resource constraint internet of things

Blackhole is one of the crucial packet-dropping attacks that can be launched on routing protocol for low-power lossy networks (RPL) protocol.In this paper, we propose an improved specification-based approach for integrating trust value in specification-based approach to detect and isolate blackhole attackers, based on a tangible value of packet-forwarding behaviour of the nodes in the network.To our knowledge, this is the first attempt to integrate packet-forwarding trust with the specification-based approach.In our proposed approach, lightweight-specification data are maintained at each device and shared periodically with the resource-rich edge device.Resource-insensitive computations are carried out at the edge device.The proposed approach uses a robust data collaboration mechanism that ensures detection-data delivery between nodes and edge devices, even in the presence of 10% of attacker nodes.Our simulations on Cooja simulator show that in an environment with 20% data loss, the proposed approach yields more than 80% true-positive rate.