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Menhir: An Oblivious Database with Protection against Access and Volume Pattern Leakage

Published: 01 July 2024 Publication History

Abstract

Analyzing user data while protecting the privacy of individuals remains a big challenge. Trusted execution environments (TEEs) are a possible solution as they protect processes and Virtual Machines (VMs) against malicious hosts. However, TEEs can leak access patterns to code and to the data being processed. Furthermore, when data is stored in a TEE database, the data volume required to answer a query is another unwanted side channel that contains sensitive information. Both types of information leaks, access patterns and volume patterns, allow for database reconstruction attacks.
In this paper, we present Menhir, an oblivious TEE database that hides access patterns with ORAM guarantees and volume patterns through differential privacy. The database allows range and point queries with SQL-like WHERE-clauses. It builds on the state-of-the-art oblivious AVL tree construction Oblix (S&P'18), which by itself does not protect against volume leakage. We show how volume leakage can be exploited in range queries and improve the construction to mitigate this type of attack. We prove the correctness and obliviousness of Menhir. Our evaluation shows that our approach is feasible and scales well with the number of rows and columns in the database.

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      cover image ACM Conferences
      ASIA CCS '24: Proceedings of the 19th ACM Asia Conference on Computer and Communications Security
      July 2024
      1987 pages
      ISBN:9798400704826
      DOI:10.1145/3634737
      Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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      Published: 01 July 2024

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      Author Tags

      1. privacy
      2. TEE database
      3. oblivious data structures
      4. access pattern leakage
      5. volume pattern leakage

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