An improved anti-forensics JPEG compression using Least Cuckoo Search algorithm

ABSTRACT

The lossy nature of the JPEG compression leaves traces which are utilized by the forensic agents to identify the local tampering in the image. In this paper, a tricky anti-forensic method has been proposed to remove the traces left by the JPEG compression in both the spatial domain and discrete cosine transform domain. A novel Least Cuckoo Search algorithm is devised in the proposed anti-forensic compression scheme. Moreover, a new fitness function called histogram deviation is formulated in the optimization algorithm. The experimentation of the proposed anti-forensic compression scheme is performed over uncompressed images from UCID database. The performance of the proposed method is evaluated, and it is compared with the existing methods using PSNR, MSE and classification accuracy as measures. The experimentation ensued with promising results, i.e. accuracy of 0.97, PSNR of 44.34 dB, and MSE of 0.1789 which prove the efficacy of the proposed method.

KEYWORDS:

• JPEG anti-forensics
• JPEG compression
• least mean square algorithm
• Cuckoo Search optimization algorithm

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Mrs. Priya M. Shelke obtained BE in Computer Engineering from University of Pune, and ME in Computer Science & Engineering from Visvesvaraya technological University, belgaum in 2002 and 2009 respectively. She is currently working as Assistant Professor in Vishwakarma Institute of Information Technology, Kondhwa, Pune. Her research interest is Image Processing.

Dr. Rajesh S. Prasad obtained BE in Computer Science & Engineering from North Maharashtra University, Jalgaon, and ME in Computer Engineering from University of Pune, Pune in 1996 and 2004 respectively. He had awarded Ph.D in Computer Science & Engineering from SRTM, Nanded in 2012. He is currently working as Professor and Principal in STES’s Sinhgad Institute of Technology and Science, Pune. His research interests are Information Retrieval and Web Mining, Fuzzy Neural Networks, Soft Computing Techniques.