Smartphone Camera De-identification while Preserving Biometric Utility

TL;DR

This paper presents a method to modify smartphone face images to hide device-specific PRNU patterns while maintaining biometric recognition accuracy, enhancing privacy and forensic capabilities.

Contribution

It introduces a DCT-based algorithm that suppresses and replaces sensor patterns in face images without affecting biometric utility.

Findings

Effective sensor anonymization demonstrated on multiple datasets

Preserves biometric matching performance

Reduces device identification accuracy using PRNU patterns

Abstract

The principle of Photo Response Non Uniformity (PRNU) is often exploited to deduce the identity of the smartphone device whose camera or sensor was used to acquire a certain image. In this work, we design an algorithm that perturbs a face image acquired using a smartphone camera such that (a) sensor-specific details pertaining to the smartphone camera are suppressed (sensor anonymization); (b) the sensor pattern of a different device is incorporated (sensor spoofing); and (c) biometric matching using the perturbed image is not affected (biometric utility). We employ a simple approach utilizing Discrete Cosine Transform to achieve the aforementioned objectives. Experiments conducted on the MICHE-I and OULU-NPU datasets, which contain periocular and facial data acquired using 12 smartphone cameras, demonstrate the efficacy of the proposed de-identification algorithm on three different PRNU-based sensor identification schemes. This work has application in sensor forensics and personal privacy.