A Report Generation Method for Defending False Negative Attacks in Ubiquitous Sensor Networks

Ye et al. proposed the statistical en-route filtering scheme to address false data injection attacks in which an adversary uses compromised nodes to inject forged reports into the network with the goal of deceiving the base station or depleting the resources of the relaying nodes. This scheme can detect such forged reports but is vulnerable to false negative attacks during the report generation process. Thus, a legitimate event may not be reported properly. In this paper, we propose a report generation method to achieve resilience in terms of false negative attacks against the report generation process of the statistical en-route filtering scheme in ubiquitous sensor networks. In the proposed method, one of the detecting nodes randomly selects several nodes to generate sensing reports and key indices to generate message authentication codes (MACs). Each of the nodes selected to produce reports generates a sensing report which contains only the matched MACs, collected from different nodes, using the keys indicated by the key indices. We analyze the security level of the proposed method under various false negative attacks against the report generation process at the end of this paper.