# Systematic Review: Anti-Forensic Computer Techniques
## 4 Results
### Weaknesses and Anti-Forensic Use Cases
Regarding novel contributions, several approaches have been proposed, including statistical modeling [69], artifact modification [71,108], parameter tuning [72], dithering [73], FSD distribution recovery [74], and DCT coefficient modification [77], as well as methods ranging from eliminating fingerprints with a high failed detection rate [69] to confusing fingerprints to hinder detection [77]. Convolutional neural networks (CNN) [75,106] and FSD distribution retrieval [105] have been proposed to identify images that have undergone anti-forensic processing. These are techniques that allow for the differentiation of manipulated images from those with single compression [105] and the detection of double-compression and related anti-forensics operations [75,106]. Others provide the modification of first-digit statistics to remove JPEG compression fingerprints based on [PERSON]'s law [76,107], while some authors propose the use of generative adversarial networks (GANs) to remove double JPEG compression fingerprints and improve image quality [78,109]. * [PERSON] et al. [110, 111, 112, 113, 114, 115] discuss anti-forensic techniques for both median filtering (MF) and image compression, some of them using generative adversarial networks (GAN). [PERSON] et al. [116] propose anti-forensic detection applied to the resampling of digital images to check if an image has undergone a resizing attempt. [PERSON] et al. [117] analyze anti-forensic techniques applied to images manipulated with GAN and present a mitigation model with CNN-based detection algorithms. [PERSON] et al. [118] develop a method by which to generate manipulated images that are indistinguishable from the originals using GAN. Some anti-forensics methods are based on GANs, as noted in papers [110; 114; 118]. These methods achieve high image quality and evade forensic detection effectively. Other articles propose approaches based on statistical analysis [112; 113] or domain modifications [115; 116]. Article [111] presents a simple method by which to classify manipulated images with anti-forensics, while article [112] proposes a forensic method by which to detect previous JPEG compressions and an improved anti-forensic method for denoising. Article [113] presents an anti-forensic method based on the discrete fractional block-shifted fractional cosine transform (DFrCT) to remove compression artifacts. Article [115] describes an anti-forensic method that adds noise specifically designed to hide the processing history of an image. Article [116] proposes a method of detecting anti-forensic resampling using partial autocorrelation coefficients. In the field of prevention, paper [117] performs a systematic review of forensic and anti-forensic methods for GAN-generated images. 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. Regarding novel contributions, papers [110; 114; 118] propose GAN-based anti-forensics methods that achieve high image quality and evade forensic detection. Article [111] presents a simple method by which to classify manipulated images with anti-forensics. Article [112] proposes a forensic method by which to detect previous JPEG compressions and an improved anti-forensic method for denoising. Article [113] presents an anti-forensic method based on the discrete fractional block-shifted fractional cosine transform (DFrCT) to remove compression artifacts. Article [115] describes an anti-forensics method that achieve high image quality and evade forensic detection. Article [111] presents a simple method by which to classify manipulated images with anti-forensics. Article [112] proposes a forensic method by which to detect previous JPEG compressions and an improved anti-forensic method for denoising. Article [113] presents an anti-forensic method based on the discrete fractional block-shifted fractional cosine transform (DFrCT) to remove compression artifacts.