计算机科学
安全多方计算
秘密分享
沙米尔的秘密分享
稳健性(进化)
密码学
异步通信
同态秘密共享
对手模型
理论计算机科学
私人信息检索
算法
计算
对手
计算机安全
计算机网络
化学
基因
生物化学
作者
Qiongxiu Li,Mads Græsbøll Christensen
标识
DOI:10.23919/eusipco.2019.8903166
摘要
Average consensus is widely used in information fusion, and it requires information exchange between a set of nodes to achieve an agreement. Unfortunately, the information exchange may disclose the individual’s private information, and this raises serious concerns for individual privacy in some applications. Hence, a privacy-preserving asynchronous averaging algorithm is proposed in this paper to maintain the privacy of each individual using Shamir’s secret sharing scheme, as known from secure multiparty computation. The proposed algorithm is based on a lightweight cryptographic technique. It gives identical accuracy solution as the non-privacy concerned algorithm and achieves perfect security in clique-based networks without the use of a trusted third party. In each iteration of the algorithm, each individual’s privacy in the selected clique is protected under a passive attack where the adversary controls some of the nodes. Finally, it also achieves robustness of up to one third transmission error.
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