RANBAR: RANSAC-based resilient aggregation in sensor networks
Proceedings of the fourth ACM workshop on Security of ad hoc and sensor networks
Cora: correlation-based resilient aggregation in sensor networks
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
A novel attack detection algorithm based on t-distribution in wireless sensor networks
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Secure encrypted-data aggregation for wireless sensor networks
Wireless Networks
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In this paper, we propose a new model of resilient data aggregation in sensor networks, where the aggregator analyzes the received sensor readings and tries to detect unexpected deviations before the aggregation function is called. In this model, the adversary does not only want to cause maximal distortion in the output of the aggregation function, but it also wants to remain undetected. The advantage of this approach is that in order to remain undetected, the adversary cannot distort the output arbitrarily, but rather the distortion is usually upper bounded, even for aggregation functions that were considered to be insecure earlier (e.g., the average). We illustrate this through an example in this paper.