Privacy-enhancing techniques and protocols for data aggregation and analytics in wireless networks require the development of novel methods for efficient and privacy-preserving computation of distributed queries with the protection of outcomes from active attackers. Previous approaches to secure privacy-preserving computation of distributed queries incur significant communication overhead and cannot be applied to big data. This paper proposes two solutions to the problem of efficient and privacy-preserving computation of distributed queries with the protection of outcomes from active outsider attackers for a new large class of distributed statistical or numerical queries. This class contains many useful statistics and is larger than other classes considered in the literature previously. We propose two protocols for the Protection of data from Active Attackers (PAA) in the case of distributed privacy-preserving computation: PAA applying Shamir’s Secret Sharing (PAA-SSS) and PAA applying homomorphic encryption (PAA-HE). The PAA-HE protocol combines the use of ElGamal and Paillier encryption schemes in one system. Theoretical analysis and experimental results show that both protocols outperform alternative approaches. PAA-HE provides stronger protection and is more efficient than PAA-SSS.

用于无线网络中的数据聚合和分析的隐私增强技术和协议需要开发新的方法来高效和保护隐私地计算分布式查询，同时保护结果免受主动攻击者的攻击。以前用于保护分布式查询的隐私保护计算的方法会产生大量的通信开销，并且不能应用于大数据。本文针对分布式查询的高效和隐私保护计算问题提出了两种解决方案，同时保护了针对新的大型分布式统计或数值查询的主动外部攻击者的结果。这个类包含许多有用的统计数据，并且比以前文献中考虑的其他类要大。在分布式隐私保护计算的情况下，我们提出了两种保护数据免受主动攻击者 (PAA) 的协议：应用 Shamir 秘密共享 (PAA-SSS) 的 PAA 和应用同态加密 (PAA-HE) 的 PAA。PAA-HE 协议在一个系统中结合了 ElGamal 和 Paillier 加密方案的使用。理论分析和实验结果表明，这两种协议都优于替代方法。PAA-HE 提供更强的保护，比 PAA-SSS 更高效。理论分析和实验结果表明，这两种协议都优于替代方法。PAA-HE 提供更强的保护，比 PAA-SSS 更高效。理论分析和实验结果表明，这两种协议都优于替代方法。PAA-HE 提供更强的保护，比 PAA-SSS 更高效。