# Systematic Review: Anti-Forensic Computer Techniques
## 4 Results
### Weaknesses and Anti-Forensic Use Cases
Article [115] describes an anti-forensics method that adds noise specifically designed to hide the processing history of an image. Article [116] proposes a method pf detecting anti-forensic resampling using partial autocorrelation coefficients. Article [117] provides a systematic review of forensic and anti-forensic methods for GAN-generated images. Finally, paper [118] proposes a dual-domain GAN-based anti-forensics (DDGAN) framework that incorporates operation-specific forensic features and machine-learned knowledge for better undetectability. * Authors such as [PERSON] et al. [119] deal with the detection of image forgery using the copy-and-paste technique. [PERSON] et al. [120; 121] discuss the same, focusing on lateral chromatic aberrations (LCA). Other authors, such as [PERSON] et al. [122], focus on the diffusion filling technique to analyze image forgeries. Article [119] presents a method of detecting copy-paste forging using \"Dyadic Wavelet SIFT\" descriptors and DoG features. On the other hand, papers [120; 121] focus on lateral chromatic aberration (LCA) as it can be manipulated to hide evidence of cut-and-paste tampering. Article [120] proposes a vector based on size differences between color channels to detect anti-forensic tampering, while [121] presents an anti-forensic method to fake LCA and disguise evidence of forging. Finally, paper [122] focuses on diffusion-based \"inpainting\" trace removal, a method of repairing or filling damaged areas in an image. Regarding contributions, paper [119] proposes a novel method of detecting detect copy-paste forging using \"Dyadic Wavelet SIFT\" descriptors and DoG features. Article [120] presents an anti-forensic method by which to manipulate lateral chromatic aberration and a vector based on channel size differences for its detection. And paper [122] proposes a novel technique by which to remove diffusion-based inpainting traces by means of noise pattern analysis and statistical models. * [PERSON] et al. [123] elaborate an alternative forensic method that uses a different type of keypoint in images to avoid anti-forensic techniques based on SIFT (scale-invariant feature transform). This paper proposes a forensic approach that counters SIFT keypoint removal by using a different type of keypoint in forensic analysis, demonstrating clear advantages over traditional SIFT keypoint-based techniques. The authors provide an innovative approach that uses a different type of keypoint in forensic analysis to overcome anti-forensic techniques that hide image manipulation. * [PERSON] et al. [124] expose a method of image tampering using a specific type of artificial neural network called a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), which makes them appear to be original. This paper proposes a novel method that uses Wasserstein-type generative adversarial networks enhanced with gradient penalty (WGAN-GP) to model image anti-forensics as an image-to-image translation problem. This multi-operation anti-forensics scheme manages to fool state-of-the-art forensic algorithms without significantly degrading image quality, and even improving it in most cases. * Other authors, such as [PERSON] et al. [125; 126], propose a universal anti-forensic scheme via adaptive substitution of the quantization table present in the images. Articles [125; 126] focus specifically on the manipulation of the quantization table in JPEG images. They come as a novelty. Article [125] proposes a universal anti-forensic scheme that adaptively replaces the quantization table, while article [126] presents a general model that replaces the quantization table for both purposes: hiding forgeries and improving the detection of existing forgeries. * [PERSON] et al. [127] analyze the contest between forensic techniques for detecting splices in audio recordings and anti-forensic techniques used to hide such splices. On the other hand, [PERSON] et al. [128] do the same with the anti-forensic technique of double audio compression. Authors such as [PERSON] et al.