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Combining Forensics and Privacy Requirements for Digital Images

Abstract : This paper proposes to study the impact of image selective encryption on both forensics and privacy preserving mechanisms. The proposed selective encryption scheme works independently on each bitplane by encrypting the s most significant bits of each pixel. We show that this mechanism can be used to increase privacy by mitigating image recognition tasks. In order to guarantee a trade-off between forensics analysis and privacy, the signal of interest used for forensics purposes is extracted from the 8−s least significant bits of the protected image. We show on the CASIA2 database that good tampering detection capabilities can be achieved for s ∈ {3,. .. , 5} with an accuracy above 80% using SRMQ1 features, while preventing class recognition tasks using CNN with an accuracy smaller than 50%.
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Contributor : Pauline Puteaux Connect in order to contact the contributor
Submitted on : Wednesday, June 16, 2021 - 11:21:37 AM
Last modification on : Tuesday, November 22, 2022 - 2:26:16 PM


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Pauline Puteaux, Vincent Itier, Patrick Bas. Combining Forensics and Privacy Requirements for Digital Images. EUSIPCO 2021 - 29th European Signal Processing Conference, Aug 2021, Dublin (virtual), Ireland. pp.806-810, ⟨10.23919/EUSIPCO54536.2021.9616041⟩. ⟨hal-03160123v2⟩



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