The Curse of Correlations for Robust Fingerprinting of Relational Databases

TL;DR

This paper reveals vulnerabilities in existing database fingerprinting methods due to inherent data correlations and proposes mitigation techniques that significantly improve robustness while maintaining data utility.

Contribution

The paper identifies correlation-based attacks on database fingerprinting and introduces mitigation techniques that enhance robustness without sacrificing data utility.

Findings

Correlation attacks can distort over 64% of fingerprint bits with minimal data modification.

Proposed mitigation techniques reduce attack impact to about 3% distortion.

Mitigation methods preserve database utility across different metrics.

Abstract

Database fingerprinting have been widely adopted to prevent unauthorized sharing of data and identify the source of data leakages. Although existing schemes are robust against common attacks, like random bit flipping and subset attack, their robustness degrades significantly if attackers utilize the inherent correlations among database entries. In this paper, we first demonstrate the vulnerability of existing database fingerprinting schemes by identifying different correlation attacks: column-wise correlation attack, row-wise correlation attack, and the integration of them. To provide robust fingerprinting against the identified correlation attacks, we then develop mitigation techniques, which can work as post-processing steps for any off-the-shelf database fingerprinting schemes. The proposed mitigation techniques also preserve the utility of the fingerprinted database considering different utility metrics. We empirically investigate the impact of the identified correlation attacks and the performance of mitigation techniques using real-world relational databases. Our results show (i) high success rates of the identified correlation attacks against existing fingerprinting schemes (e.g., the integrated correlation attack can distort 64.8\% fingerprint bits by just modifying 14.2\% entries in a fingerprinted database), and (ii) high robustness of the proposed mitigation techniques (e.g., with the mitigation techniques, the integrated correlation attack can only distort $3\%$ fingerprint bits).