VAL

Volume and Access Pattern Leakage-Abuse Attack with Leaked Documents

Conference Paper (2022)
Author(s)

Steven Lambregts (Student TU Delft)

Huanhuan Chen (TU Delft - Cyber Security)

Jianting Ning (Fujian Normal University, Singapore Management University)

Kaitai Liang (TU Delft - Cyber Security)

Research Group
Cyber Security
Copyright
© 2022 Steven Lambregts, H. Chen, Jianting Ning, K. Liang
DOI related publication
https://doi.org/10.1007/978-3-031-17140-6_32
More Info
expand_more
Publication Year
2022
Language
English
Copyright
© 2022 Steven Lambregts, H. Chen, Jianting Ning, K. Liang
Research Group
Cyber Security
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
653-676
ISBN (print)
978-3-031-17139-0
ISBN (electronic)
978-3-031-17140-6
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Searchable Encryption schemes provide secure search over encrypted databases while allowing admitted information leakages. Generally, the leakages can be categorized into access and volume pattern. In most existing SE schemes, these leakages are caused by practical designs but are considered an acceptable price to achieve high search efficiency. Recent attacks have shown that such leakages could be easily exploited to retrieve the underlying keywords for search queries. Under the umbrella of attacking SE, we design a new Volume and Access Pattern Leakage-Abuse Attack (VAL-Attack) that improves the matching technique of LEAP (CCS ’21) and exploits both the access and volume patterns. Our proposed attack only leverages leaked documents and the keywords present in those documents as auxiliary knowledge and can effectively retrieve document and keyword matches from leaked data. Furthermore, the recovery performs without false positives. We further compare VAL-Attack with two recent well-defined attacks on several real-world datasets to highlight the effectiveness of our attack and present the performance under popular countermeasures.

Files

978_3_031_17140_6_32.pdf
(pdf | 1.71 Mb)
- Embargo expired in 01-07-2023
License info not available