Anti-forensics of Median Filtering and Contrast Enhancement, Journal of Visual Communication and Image Representation
The paper proposes an anti-forensic technique to counter spatial domain forensic detectors and demonstrates it's accuracy on popular image manipulation operations such as median filtering and contrast enhancement. The proposed optimization modifies the image so as to incorporate the median filtering or contrast enhancement operation while ensuring that the image's spatial characteristics do not change significantly.
Median filter detector results for (a) median filtered vs source image. (b) anti-forensically modified vs source image.
Contrast enhancement detector results for (a) source image. (b) contrast enhanced image. (c) anti-forensically modified image.

Anti-forensic technique for median filtering using L1 - L2 TV model, IEEE International Workshop on Information Forensics and Security (WIFS 2016)
The paper proposes an anti-forensic technique for countering Median filtering forensics. The counter forensic attack is formulated as an optimization problem, constrained by the difference in Anisotropic and Isotropic Total Variation regularization. The optimization is written as difference of convex components and is solved using Split Bregman technique.