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Efficient and Provably Secure Aggregation of Encrypted Data in Wireless Sensor Networks

机译:无线传感器网络中有效且安全的加密数据聚合

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Wireless sensor networks (WSNs) are composed of tiny devices with limited computation and battery capacities. For such resource-constrained devices, data transmission is a very energy-consuming operation. To maximize WSN lifetime, it is essential to minimize the number of bits sent and received by each device. One natural approach is to aggregate sensor data along the path from sensors to the sink. Aggregation is especially challenging if end-to-end privacy between sensors and the sink (or aggregate integrity) is required. In this article, we propose a simple and provably secure encryption scheme that allows efficient additive aggregation of encrypted data. Only one modular addition is necessary for ciphertext aggregation. The security of the scheme is based on the indistinguishability property of a pseudorandom function (PRF), a standard cryptographic primitive. We show that aggregation based on this scheme can be used to efficiently compute statistical values, such as mean, variance, and standard deviation of sensed data, while achieving significant bandwidth savings. To protect the integrity of the aggregated data, we construct an end-to-endrnaggregate authentication scheme that is secure against outsider-only attacks, also based on the indistinguishability property of PRFs.
机译:无线传感器网络(WSN)由计算量和电池容量有限的微型设备组成。对于此类资源受限的设备,数据传输是非常耗能的操作。为了最大程度地延长WSN寿命,必须将每个设备发送和接收的位数最小化。一种自然的方法是沿从传感器到接收器的路径聚合传感器数据。如果需要传感器与接收器之间的端到端私密性(或聚合完整性),聚合将特别具有挑战性。在本文中,我们提出了一种简单且可证明安全的加密方案,该方案允许对加密数据进行有效的累加聚合。密文聚合只需要添加一个模块。该方案的安全性基于伪随机函数(PRF)(标准密码原语)的不可区分性。我们表明,基于此方案的聚合可用于有效地计算统计值,例如感测数据的均值,方差和标准偏差,同时实现显着的带宽节省。为了保护聚合数据的完整性,我们还基于PRF的不可区分性,构造了一种端对端聚合身份验证方案,该方案可防止仅局外人攻击。

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