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Communication Dans Un Congrès Année : 2017

Information leakage analysis of inner-product functional encryption based data classification

Résumé

In this work, we study the practical security of inner- product functional encryption. We left behind the mathematical security proof of the schemes, provided in the literature, and focus on what attackers can use in realistic scenarios without tricking the protocol, and how they can retrieve more than they should be able to. This study is based on the proposed protocol from [1]. We generalised the scenario to an attacker possessing n secret keys. We proposed attacks based on machine learning, and experiment them over the MNIST dataset [2].
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Dates et versions

hal-01802702 , version 1 (29-05-2018)

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Damien Ligier, Sergiu Carpov, Caroline Fontaine, Renaud Sirdey. Information leakage analysis of inner-product functional encryption based data classification. PST'17 : 15th International Conference on Privacy, Security and Trust, Aug 2017, Calgary, Canada. ⟨10.1109/PST.2017.00043⟩. ⟨hal-01802702⟩
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