A False Data Filtering Scheme Using Cluster-Based Organization in Sensor Networks
In sensor networks, the adversaries can inject false data reports from compromising nodes. Previous approaches for filtering false reports share keys between the source node and its upstream nodes on the path to sink, and rely on intermediate nodes to verify the reports generated by downstream nodes in a probabilistic manner. As a result, false reports have to travel several hops before detected. Worse still, these schemes haven't balanced the overheads of all nodes in the process of keys distributing. In response to these, this paper proposes a scheme, referred to as Cluster-based False data Filtering Scheme (CFFS), in which nodes are grouped into clusters and a sink-rooted tree of cluster heads is constructed.