Developing realistic attack models for privacy preserving record linkage and algorithms to prevent such attacks
Final Report Abstract
The project focused on attacks against methods that combine multiple databases containing personal data using specialized record linkage techniques (’privacy-preserving record-linkage’, PPRL). Initially, the effectiveness of existing attacks was examined under more realistic conditions than those typically used in literature scenarios. This particularly includes the assumption that the attacker possesses a plaintext dataset with an identical frequency distribution of identifiers. Under such real-world conditions, the probability of success is significantly lower than that suggested by previous literature. It was also demonstrated that the success probabilities of an attack can be significantly reduced by using subgroup-specific encryptions (’salting’). Subsequently, a new PPRL method was developed that leads to significantly greater security against attacks by applying a classical idea from cryptography: diffusion. This work provides the first analytical estimates of the security of such methods in general. Finally, it was shown that the method used by German cancer registries is more vulnerable to almost trivial attacks than previous publications had suggested.
Publications
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On the effectiveness of graph matching attacks against privacy-preserving record linkage. PLOS ONE, 17(9), e0267893.
Heng, Youzhe; Armknecht, Frederik; Chen, Yanling & Schnell, Rainer
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Salting as a Countermeasure against Attacks on Privacy Preserving Record Linkage Techniques. Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, 353-360. SCITEPRESS - Science and Technology Publications.
Chen, Yanling; Schnell, Rainer; Armknecht, Frederik & Heng, Youzhe
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Strengthening Privacy-Preserving Record Linkage using Diffusion. Proceedings on Privacy Enhancing Technologies, 2023(2), 298-311.
Armknecht, Frederik; Heng, Youzhe & Schnell, Rainer
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Cryptanalysis of the Record Linkage Protocol Used by German Cancer Registries. In S. Wendzel, C. Wressnegger, L. Hart mann, F. Freiling, F. Armknecht & L. Reinfelder (Hrsg.), Sicherheit 2024 (S. 65–74)
Heng, Y., Schnell, R. & Armknecht, F.
