On the Mitigation of Controllable Event Triggering Attack in WSNs
Haoran Hu, Wei Chang · 2020
Compressive sensing-based data collecting is a promising technique, which can significantly reduce the communication costs in wireless sensor networks (WSNs). However, a recent study shows that it is vulnerable to controllable event triggering attack (CETA): after compromising a sensor and carefully manipulating the environmental elements around a target in the subtree rooted at the sensor, an attacker is able to infer sensitive parameters of the target. The existing countermeasure is purely based on cryptography and requires central control. In this paper, we propose a lightweight non-cryptography-based approach by termly modifying the structure of the data gathering tree. However, how to efficiently and effectively construct the tree is an open problem. To solve the problem, we create a novel topology-based coding scheme and a distributed algorithm to mitigate the CETA attack. By adopting this approach, the time for successfully launching a CETA attack is significantly increased. Extensive simulations show that our solution can efficiently and securely build different data gathering trees for consecutive sensing tasks.