Secure Outsourced Private Set Intersection with Linear Complexity

Sumit Kumar Debnath, Kouchi Sakurai, Kunal Dey, Nibedita Kundu

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

5 被引用数 (Scopus)

抄録

In the context of privacy preserving protocols, Private Set Intersection (PSI) plays an important role due to their wide applications in recent research community. In general, PSI involves two participants to securely determine the intersection of their respective input sets, not beyond that. These days, in the context of PSI, it is become a common practice to store datasets in the cloud and delegate PSI computation to the cloud on outsourced datasets, similar to secure cloud computing. We call this outsourced PSI as OPSI. In this paper, we design a new construction of OPSI in malicious setting under the Decisional Diffie-Hellman (DDH) assumption without using any random oracle. In particular, our OPSI is the first that incurs linear complexity in malicious environment with not-interactive setup. Further, we employ a random permutation to extend our OPSI to its cardinality variant OPSI-CA. In this case, all the properties remain unchanged except that the adversarial model is semi-honest instead of malicious.

本文言語英語
ホスト出版物のタイトル2021 IEEE Conference on Dependable and Secure Computing, DSC 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728175348
DOI
出版ステータス出版済み - 1月 30 2021
イベント2021 IEEE Conference on Dependable and Secure Computing, DSC 2021 - Aizuwakamatsu, Fukushima, 日本
継続期間: 1月 30 20212月 2 2021

出版物シリーズ

名前2021 IEEE Conference on Dependable and Secure Computing, DSC 2021

会議

会議2021 IEEE Conference on Dependable and Secure Computing, DSC 2021
国/地域日本
CityAizuwakamatsu, Fukushima
Period1/30/212/2/21

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • 情報システムおよび情報管理
  • 安全性、リスク、信頼性、品質管理

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