Abstract: One of the key characteristics of digital images with a discrete representation is its pliability to manipulation. Recent trends in the field of unsupervised detection of digital forgery includes several advanced strategies devoted to reveal anomalies just considering several aspects of multimedia content. One of the promising approach, among others, considers the possibility to exploit the statistical distribution of DCT coefficients in order to reveal the irregularities due to the presence of a superimposed signal over the original one (e.g., copy and paste). As recently proved the ratio between the quantization tables used to compress the signal before and after the malicious forgery alter the histograms of the DCT coefficients especially for some basis that are close in terms of frequency content. In this work we analyze in more details the performances of existing approaches evaluating their effectiveness by making use of different input datasets with respect to resolution size, compression ratio and just considering different kind of forgeries (e.g., presence of duplicate regions or images composition). We also present possible post-processing techniques able to manipulate the forged image just to reduce the performance of the current state-of-art solution. Finally we conclude the papers providing future improvements devoted to increase robustness and reliability of forgery detection into DCT domain.

  publisher    = {ACM Press},
  author       = {Sebastiano Battiato and Giuseppe Messina},
  url          = {http://www.sheridanprinting.com/acm/mm/files/mifor05a-battiato1.pdf},
  year         = {2009},
  pages        = {37--42},
  address      = {New York},
  title        = {Digital forgery estimation into {DCT} domain: a critical analysis},
  booktitle    = {Proceedings of the First ACM Workshop on Multimedia in Forensics},