Authentication of JPEG Images Based on Genetic Algorithms



Venkata Gopal Edupuganti , Frank Y. Shih *
Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA


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© 2017 Shih et al.;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA; Tel: 973-596-5654; Fax: 973-596-5777; E-mail: frank.y.shih@njit.edu


Abstract

This paper presents an efficient authentication method for JPEG images based on Genetic Algorithms (GA). The current authentication methods for JPEG images require the receivers to know the quantization table beforehand in order to authenticate the images. Moreover, the quantization tables used in the JPEG compression are different for different quality factors, thus increasing the burden on the receivers to maintain several quantization tables. We propose a novel GA-based method which possesses three advantages. First, the computation at the receiver end is simplified. Second, it is no more required for the receivers to maintain quantization tables. Third, the method is resistant against Vector Quantization (VQ) and Copy-Paste (CP) attacks by generating the authentication information which is unique with respect to each block and each image. Furthermore, we develop a two- level detection strategy to reduce the false acceptance ratio of invalid blocks. Experimental results show that the proposed GA-based method can successfully authenticate JPEG images under variant attacks.

Keywords: Watermarking, genetic algorithm, authentication, vector quantization.