Privacy preserving set intersection protocol secure against malicious behaviors

Yingpeng Sang, Hong Shen

研究成果: Conference contribution同行評審

26 引文 斯高帕斯(Scopus)

摘要

When datasets are distributed on different sources, finding out their intersection while preserving the privacy of the datasets is a widely required task. In this paper, we address the Privacy Preserving Set Intersection (PPSI) problem, in which each of the N parties learns no elements other than the intersection of their N private datasets. We propose an efficient protocol in the malicious model, where the adversary may control arbitrary number of parties and execute the protocol for its own benefit. A related work in [12] has a correctness probability of (N-1/N)N (N is the size of the encryption scheme's plaintext space), a computation complexity of O(N2S 2lgN) (S is the size of each party's data set). Our PPSI protocol in the malicious model has a correctness probability of (N-1/N)N-1, and achieves a computation cost of O(c2S2lgN) (c is the number of malicious parties and c ≤ N - 1).

原文English
主出版物標題18th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2007
頁面461-468
頁數8
DOIs
出版狀態Published - 2007
對外發佈
事件18th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2007 - Adelaide, SA, Australia
持續時間: 3 12月 20076 12月 2007

出版系列

名字Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings

Conference

Conference18th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2007
國家/地區Australia
城市Adelaide, SA
期間3/12/076/12/07

指紋

深入研究「Privacy preserving set intersection protocol secure against malicious behaviors」主題。共同形成了獨特的指紋。

引用此