Cfp: Enabling Camera Fingerprint Concealment For Privacy-Preserving Image Sharing

It has been discovered that every photo carries an unique hardware fingerprint of the photographing digital camera. This camera fingerprint is remarkably effective in image-to-camera matching and has been applied in a wide variety of beneficial forensic tasks such as copyright protection and integrity validation. However, the fingerprints carried by the images can also be utilized for malicious purposes. An adversary can launch identity linking attack, which re-identifies the anonymous social network accounts, through exploiting the digital cameras' fingerprints that are carried by the posted images. Moreover, the adversary can easily frame an innocent victim or bypass camera-based smartphone authentication systems by launching identity forgery attacks, i.e., fabricating unoriginal fingerprints onto images.Currently, no effective counter measures against such attacks have been proposed yet. To solve this problem, in this paper, we first evaluate the effectiveness of the attacks in the current image sharing practices. We then propose CFP, an intermediary between smartphone users and image sharing platforms that conceals the camera fingerprint of the photographing device. Instead of removing the camera fingerprint from the image of interest, our system protects user privacy through obfuscating the camera fingerprint with a specially designed random perturbation component. With such design, the proposed system is enabled to prevent malicious utilizations of camera fingerprint while preserving the beneficial applications. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the CFP system on various social platforms. Using the CFP obfuscated images, the True Positive Rate of identity linking attacks is reduced by around 85%. For identity forgery attacks, our system enables an effective detection mechanism that could achieve 100% detection rate.