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Secure Top-k Inner Product Retrieval

Published: 17 October 2018 Publication History

Abstract

Secure top-k inner product retrieval allows the users to outsource encrypted data vectors to a cloud server and at some later time find the k vectors producing largest inner products giving an encrypted query vector. Existing solutions suffer poor performance raised by the client's filtering out top-k results. To enable the server-side filtering, we introduce an asymmetric inner product encryption AIPE that allows the server to compute inner products from encrypted data and query vectors. To solve AIPE's vulnerability under known plaintext attack, we present a packing approach IP Packing that allows the server to obtain the entire set of inner products between the query and all data vectors but prevents the server from associating any data vector with its inner product. Based on IP Packing, we present our solution SKIP to secure top-k inner product retrieval that further speeds up retrieval process using sequential scan. Experiments on real recommendation datasets demonstrate that our protocols outperform alternatives by several orders of magnitude.

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Cited By

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  • (2024)Relational Algorithms for Top-k Query EvaluationProceedings of the ACM on Management of Data10.1145/36549712:3(1-27)Online publication date: 30-May-2024
  • (2024)Secure and Efficient Similarity Retrieval in Cloud Computing Based on Homomorphic EncryptionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335090919(2454-2469)Online publication date: 2024
  • (2024)KMSQ: Efficient and Privacy-Preserving Keyword-Oriented Multidimensional Similarity Query in eHealthcareIEEE Internet of Things Journal10.1109/JIOT.2023.331733411:5(7918-7934)Online publication date: 1-Mar-2024
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cover image ACM Conferences
CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management
October 2018
2362 pages
ISBN:9781450360142
DOI:10.1145/3269206
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 17 October 2018

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Author Tags

  1. inner product encryption
  2. known plaintext attack
  3. top-k retrieval

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CIKM '18 Paper Acceptance Rate 147 of 826 submissions, 18%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

View all
  • (2024)Relational Algorithms for Top-k Query EvaluationProceedings of the ACM on Management of Data10.1145/36549712:3(1-27)Online publication date: 30-May-2024
  • (2024)Secure and Efficient Similarity Retrieval in Cloud Computing Based on Homomorphic EncryptionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335090919(2454-2469)Online publication date: 2024
  • (2024)KMSQ: Efficient and Privacy-Preserving Keyword-Oriented Multidimensional Similarity Query in eHealthcareIEEE Internet of Things Journal10.1109/JIOT.2023.331733411:5(7918-7934)Online publication date: 1-Mar-2024
  • (2023)SetRkNN: Efficient and Privacy-Preserving Set Reverse kNN Query in CloudIEEE Transactions on Information Forensics and Security10.1109/TIFS.2022.323178518(888-903)Online publication date: 2023
  • (2023)Efficient crowdsourced best objects finding via superiority probability based ordering for decision support systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.119893223:COnline publication date: 1-Aug-2023
  • (2023)Machine Intelligence in Pancreatic CancerHandbook of Cancer and Immunology10.1007/978-3-030-80962-1_317-1(1-29)Online publication date: 3-Nov-2023
  • (2022)Privacy-Preserving Top-k Spatio-Textual Similarity Join2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom56396.2022.00102(718-726)Online publication date: Dec-2022
  • (2022)Achieving Efficient and Privacy-Preserving Set Containment Search Over Encrypted DataIEEE Transactions on Services Computing10.1109/TSC.2021.306524015:5(2604-2618)Online publication date: 1-Sep-2022
  • (2022)Efficient and Privacy-Preserving Similarity Query With Access Control in eHealthcareIEEE Transactions on Information Forensics and Security10.1109/TIFS.2022.315239517(880-893)Online publication date: 2022
  • (2022)Efficient and Privacy-Preserving Similarity Range Query Over Encrypted Time Series DataIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.306161119:4(2501-2516)Online publication date: 1-Jul-2022
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