Fraud and Tamper Detection in Authenticity Verification through Gradient Based Image Reconstruction Technique for Security Systems

Abstract

Authenticity verification for security systems is a very important research problem with respect to information security. One of the principal problems in image forensics is determining if a particular image is authentic or not. This can be a crucial task when images are used as basic evidence to influence judgment like, for example, in a court of law. Image editing software like Adobe Photoshop, Maya etc. and technically advanced digital photography are used to edit, manipulate or tamper the images easily without living obvious visual clues. The abusive use of digital forgeries has become a serious problem in various fields like authenticity verification, medical imaging, digital forensic, journalism, scientific publications etc. To carry out such forensic analysis, various technological instruments have been developed in the literature. In this paper the problem of detecting if an image has been forged is investigated. To detect tampering and forging, a novel methodology based on gradient based image reconstruction is proposed. Our method verifies the authenticity of image in two phases- modeling phase; where the image is reconstructed from its gradients by solving a poisson equation and forming a knowledge based model and simulation phase; where the absolute difference method and histogram matching criterion between the original and test image is used. Such a method allows concluding that if a tampering has occurred. Experimental results are presented to demonstrate the performance of our gradient- based image reconstruction approach and confirm that the technique is able to verify whether a forged image is presented to a security system for authenticity verification. Through this unique mechanism, one can secure the most reliable information and forging or tampering of images for gaining false authentication and hence fraud can be detected.