A Pair-wise Key Distribution Mechanism and Distributed Trust Evaluation Model for Secure Data Aggregation in Mobile Sensor Networks
This addresses security and reliability issues for mobile sensor networks, though it appears incremental by combining existing techniques like key establishment and statistical outlier detection.
The authors tackled secure data aggregation in mobile sensor networks by proposing a framework with pair-wise key distribution and a distributed trust evaluation model, which filtered erroneous data from compromised nodes and prevented it from reaching the sink, as validated through simulations.
We propose a secure data aggregation (SDA) framework for mobile sensor networks whose topology changes dynamically with time. The SDA framework (designed to be resilient to both insider and outsider attacks) comprises of a pair-wise key establishment mechanism run along the edges of a data gathering tree and a distributed trust evaluation model that is tightly integrated with the data aggregation process itself. If an aggregator node already shares a secret key with its child node, the two nodes locally coordinate to refresh and establish a new pair-wise secret key; otherwise, the aggregator node requests the sink to send a seed-secret key message that is used as the basis to establish a new pair-wise secret key. The trust evaluation model uses the two-sided Grubbs test to identify outlier data in the periodic beacons collected from the child nodes (neighbor) nodes. Once the estimated trust score for a neighbor node falls below a threshold, the sensor node locally classifies its neighbor node as a Compromised or Faulty (CF) node, and discards the data or aggregated data received from the CF node. This way, the erroneous data generated by the CF nodes could be filtered at various levels of the data gathering tree and are prevented from reaching the root node (sink node). Finally, we assess the effectiveness of our trust evaluation model through a comprehensive simulation study.