PP-PRNU: PRNU-based source camera attribution with privacy-preserving applications

Tracing the origin of digital images is a crucial concern in digital image forensics, where accurately identifying the source of an image is essential that leads important clues to investing and law enforcement agencies. Photo Response Non-Uniformity (PRNU) based camera attribution is an effective forensic tool for identifying the source camera of a crime scene image. The PRNU pattern approach helps investigators determine whether a specific camera captured a crime scene image using the Pearson correlation coefficient between the unique camera fingerprint and the PRNU noise. However, this approach raises privacy concerns as the camera fingerprint or the PRNU noise can be linked to non-crime images taken by the camera, potentially disclosing the photographer’s identity. To address this issue, we propose a novel PRNU-based source camera attribution scheme that enables forensic investigators to conduct criminal investigations while preserving privacy. In the proposed scheme, a camera fingerprint extracted from a set of known images and PRNU noise extracted from the anonymous image are divided into multiple shares using Shamir’s Secret Sharing (SSS). These shares are distributed to various cloud servers where correlation is computed on a share basis between the camera fingerprint and the PRNU noise. The partial correlation values are combined to obtain the final correlation value, determining whether the camera took the image. The security analysis and the experimental results demonstrate that the proposed scheme not only preserves privacy and ensures data confidentiality and integrity, but also is computationally efficient compared to existing methods. Specifically, the results showed that our scheme achieves similar accuracy in source camera attribution with a negligible decrease in performance compared to non-privacy-preserving methods and is computationally less expensive than state-of-the-art schemes. Our work advances research in image forensics by addressing the need for accurate source identification and privacy protection. The privacy-preserving approach is beneficial for scenarios where protecting the identity of the photographer is crucial, such as in whistleblower cases.