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. This paper proposes 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.