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Photo Response Non-Uniformity(PRNU) noise has proven to be very effectivetool in camera based forensics. It helps to match a photo to the device thatclicked it. In today's scenario, where millions and millions of images areuploaded every hour, it is very easy to compute this unique PRNU pattern from acouple of shared images on social profiles. This endangers the privacy of thecamera owner and becomes a cause of major concern for the privacy-awaresociety. We propose SSS-PRNU scheme that facilitates the forensic investigatorsto carry out their crime investigation without breaching the privacy of thepeople. Thus, maintaining a balance between the two. To preserve privacy,extraction of camera fingerprint and PRNU noise for a suspicious image iscomputed in a trusted execution environment such as ARM TrustZone. Afterextraction, the sensitive information of camera fingerprint and PRNU noise isdistributed into multiple obfuscated shares using Shamir secret sharing(SSS)scheme. These shares are information-theoretically secure and leak noinformation of underlying content. The encrypted information is distributed tomultiple third-part servers where correlation is computed on a share basisbetween the camera fingerprint and the PRNU noise. These partial correlationvalues are combined together to obtain the final correlation value that becomesthe basis for a match decision. Transforming the computation of the correlationvalue in the encrypted domain and making it well suited for a distributedenvironment is the main contribution of the paper. Experiment results validatethe feasibility of the proposed scheme that provides a secure framework forPRNU based source camera attribution. The security analysis and evaluation ofcomputational and storage overheads are performed to analysis the practicalfeasibility of the scheme.

SSS-PRNU: Privacy-Preserving PRNU Based Camera Attribution using Shamir Secret Sharing