TENSOR EU Project

Part of EU Open Research Repository
Published March 2, 2024 | Version v1
Conference paper Open

Query Recovery from Easy to Hard: Jigsaw Attack against SSE

Authors/Creators

  • 1. ROR icon Huazhong University of Science and Technology
  • 2. Hubei Key Laboratory of Distributed System Security
  • 3. JinYinHu Laboratory
  • 4. ROR icon State Key Laboratory of Cryptology
  • 5. ROR icon St. Francis Xavier University
  • 6. ROR icon Delft University of Technology

Description

Searchable symmetric encryption schemes often unintentionally disclose certain sensitive information, such as access, volume, and search patterns. Attackers can exploit such leakages and other available knowledge related to the user's database to recover queries. We find that the effectiveness of query recovery attacks depends on the volume/frequency distribution of keywords. Queries containing keywords with high volumes/frequencies are more susceptible to recovery, even when countermeasures are implemented. Attackers can also effectively leverage these ``special'' queries to recover all others.
By exploiting the above finding, we propose a Jigsaw attack that begins by accurately identifying and recovering those distinctive queries. Leveraging the volume, frequency, and co-occurrence information, our attack achieves 90% accuracy in three tested datasets, which is comparable to previous attacks (Oya et al., USENIX' 22 and Damie et al., USENIX' 21). With the same runtime, our attack demonstrates an advantage over the attack proposed by Oya et al (approximately 15% more accuracy when the keyword universe size is 15k). Furthermore, our proposed attack outperforms existing attacks against widely studied countermeasures, achieving roughly 60% and 85% accuracy against the padding and the obfuscation, respectively. In this context, with a large keyword universe (≥3k), it surpasses current state-of-the-art attacks by more than 20%

Files

Query Recovery from Easy to Hard Jigsaw Attack against SSE.pdf

Files (3.2 MB)

Additional details

Identifiers

URL
https://arxiv.org/abs/2403.01155

Funding

European Commission
TENSOR - Reliable biomeTric tEhNologies to asSist Police authorities in cOmbating terrorism and oRganized crime 101073920
European Commission
TANGO - Digital Technologies ActiNg as a Gatekeeper to information and data flOws 101070052
European Commission
REWIRE - REWiring the ComposItional Security VeRification and AssurancE of Systems of Systems Lifecycle 101070627
Ministry of Science and Technology of the People's Republic of China
National Key Research and Development Program of China No. 2021YFB3101304
National Natural Science Foundation of China
National Natural Science Foundation of China No. 62372201
National Natural Science Foundation of China
National Natural Science Foundation China No. 62272186

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