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Multi-Party Private Set Intersection: A Circuit-Based Protocol with Jaccard Similarity for Secure and Efficient Anomaly Detection in Network Traffic

  • Jiuheng Su
  • , Zhili Chen*
  • , Xiaomin Yang
  • *此作品的通讯作者
  • East China Normal University
  • Shanghai Jiao Tong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

We present a new circuit-based protocol for multi-party private set intersection (PSI) that allows m parties to compute the intersection of their datasets without revealing any additional information about the items outside the intersection. Building upon the two-party Sort-Compare-Shuffle (SCS) protocol, we seamlessly extend it to a multi-party setting. Demonstrating its practicality through implementation, our protocol exhibits acceptable performance. Specifically, with 7 parties, each possessing a set size of {2}^{12}$ ?></TexMath><File name="a00 - inline2"type="gif"/></Formula>, our protocol completes in just 19 seconds. Moreover, circuit-based protocols like ours have an advantage over using custom protocols to perform more complex computation. We substantiate this advantage by incorporating a module for calculating the Jaccard similarity metric of the private sets which can be used in the application domain of network traffic analysis for anomaly detection. This extension showcases the versatility of our protocol beyond set intersection computations, demonstrating its efficacy in preserving privacy while efficiently identifying abnormal patterns in network flow.

源语言英语
主期刊名Proceedings of 2024 3rd International Conference on Cryptography, Network Security and Communication Technology, CNSCT 2024
出版商Association for Computing Machinery
361-366
页数6
ISBN(电子版)9798400716959
DOI
出版状态已出版 - 19 1月 2024
活动3rd International Conference on Cryptography, Network Security and Communication Technology, CNSCT 2024 - Virtual, Online, 中国
期限: 19 1月 202421 1月 2024

出版系列

姓名ACM International Conference Proceeding Series

会议

会议3rd International Conference on Cryptography, Network Security and Communication Technology, CNSCT 2024
国家/地区中国
Virtual, Online
时期19/01/2421/01/24

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