Secure Determining of the k-th Greatest Element Among Distributed Private Values

M. Jaberi, H. Mala
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Abstract

One of the basic operations over distributed data is to find the k-th greatest value among union of these numerical data. The challenge arises when the datasets are private and their owners cannot trust any third party. In this paper, we propose a new secure protocol to find the k-th greatest value by means of secure summation sub-protocol. We compare our proposed protocol with other similar protocols. Specially, we will show that our scheme is more efficient than the well-known protocol of Aggarwal et.al. (2004) in terms of computation and communication complexity. Specifically, in the case of Ti = 1 secret value for any party Pi our protocol has log m computation overhead and δ log m communication overhead for party Pi, where m and δ are the maximum acceptable value and communication overhead of the secure summation sub-protocol, respectively. The overheads of our protocol is exactly half of the overheads of Aggarwal’s protocol.
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分布私有值中第k大元素的安全确定
分布数据的基本运算之一是求这些数值数据的并集的第k个最大值。当数据集是私有的,并且它们的所有者不能信任任何第三方时,挑战就出现了。本文提出了一种利用安全求和子协议寻找第k个最大值的新安全协议。我们将所提出的协议与其他类似协议进行了比较。特别地,我们将证明我们的方案比众所周知的Aggarwal等协议更有效。(2004)在计算和通信复杂性方面。具体来说,在任何一方Pi的Ti = 1秘密值的情况下,我们的协议对Pi的计算开销为log m,通信开销为δ log m,其中m和δ分别是安全求和子协议的最大可接受值和通信开销。我们协议的开销恰好是Aggarwal协议开销的一半。
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