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A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks

机译:基于压缩感知的自适应安全数据收集方案,用于分布式无线传感器网络

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Toward the goal of high security and efficiency for data collection in wireless sensor network, this article proposed an adaptable secure compressive sensing–based data collection scheme for distributed wireless sensor network. It adopted public key cryptography technology to solve the key distribution problem, and compressive sensing over finite fields to reduce the communication cost of data collection. Under hardness of decisional learning with errors problem on lattice, it can ensure indistinguishability against chosen ciphertext attack (IND-CCA1) security scheme for collected data on the extranet and indistinguishability against chosen plaintext attack security for data during the process of distributed collection on the intranet. Owing to the similar linear structure for lattices and compressive sensing, data encryption collection can be all in the form of efficient linear operations, and internode data aggregation can be in the form of addition operation.
机译:为了实现无线传感器网络中数据收集的高安全性和高效率的目标,本文提出了一种适用于分布式无线传感器网络的基于安全压缩感知的自适应数据收集方案。它采用公钥加密技术解决了密钥分配问题,并在有限域上进行了压缩感知,以降低数据收集的通信成本。在网格上具有错误问题的决策学习的严格性下,它可以确保针对Extranet上收集的数据的针对所选密文攻击(IND-CCA1)安全方案的不可区分性,以及针对Intranet上的数据收集的针对所选明文攻击安全性的不可区分性。由于晶格和压缩感测的线性结构相似,因此数据加密收集可以全部采用有效的线性运算形式,而节点间数据聚合则可以采用加法运算形式。

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