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A False Data Filtering Scheme Using Cluster-Based Organization in Sensor Networks

机译:传感器网络中基于集群组织的虚假数据过滤方案

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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 cluster-based filtering scheme, in which nodes are grouped into clusters once deployed by employing some strong nodes act as cluster heads. We then proposed a distributed method of keys assignment by constructing a sink-rooted tree which comprises of all the cluster heads, guarantees that the keys of a source cluster are stored by several forwarding clusters close to it and thus to filter false reports generated by the source cluster during several hops during forwarding, further, the number of authentication keys held by the forwarding clusters getting smaller with the distance increase from the source cluster and thus to balance the keys stored by each forwarding cluster. Analysis and simulation results show that our scheme outperforms existing schemes in terms of overhead balance and filtering efficiency.
机译:在传感器网络中,攻击者可以从受到威胁的节点注入错误的数据报告。先前的过滤错误报告的方法在源节点及其上游节点之间共享密钥以陷入,并依赖中间节点以概率方式验证下游节点生成的报告。结果,虚假报告必须经过几跳才能被检测到。更糟糕的是,这些方案并未在密钥分配过程中平衡所有节点的开销。针对这些问题,本文提出了一种基于集群的过滤方案,该方案中,一旦采用一些强大的节点作为集群头,则将节点分组为集群。然后,我们通过构造一个包含所有群集头的宿根树来提出一种分布式的密钥分配方法,确保源群集的密钥由靠近它的几个转发群集存储,从而过滤由源群集生成的错误报告。源群集在转发过程中经过多次跃点时,进一步地,随着与源群集的距离增加,转发群集所持有的身份验证密钥的数量会越来越少,从而平衡每个转发群集存储的密钥。分析和仿真结果表明,我们的方案在开销平衡和过滤效率方面优于现有方案。

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