# Recent Advances in Digital Image and Video Forensics, Anti-forensics and Counter Anti-forensics

**Authors:** Maryam Al-Fehani, Saif Al-Kuwari  
**arXiv:** [2402.02089](https://arxiv.org/abs/2402.02089)  
**Date:** 2024-02-03  
**Summary page:** https://www.summarizepaper.com/en/paper/2402.02089v1/

## Key points

- Image and video forensics are increasingly important due to widespread manipulation of digital media on social media platforms, leading to the spread of disinformation and fake news.
- The survey delves into image and video identification, forgery detection, manipulated digital media, and generative media.
- The paper is structured into two main sections: Section 3 focuses on image forensics, while Section 4 delves into video forensics.
- Each section covers detection methods (Sections 3.1, 3.2, 4.1, and 4.2), anti-forensics methods (Sections 3.3 and 4.3), as well as counter anti-forensics methods (Sections 3.4 and 4.4).
- Commonly used datasets in image and video forensics research vary in size and contain a mix of real and fake images or videos for analysis.
- Objectives of the survey include providing an up-to-date review of state-of-the-art research in image and video forensics, examining generative images, analyzing anti-forensic strategies along with countermeasures.
- A comparison table is presented to showcase the coverage of various techniques across different surveys related to image and video forensics research.
- The comprehensive overview aims to shed light on challenges faced in detecting manipulated digital media effectively while paving the way for promising future directions in this field.

## Summary

Image and video forensics have become increasingly important in light of the widespread manipulation of digital media on social media platforms. This has led to the spread of disinformation and fake news. In response to this issue, this survey delves into the realm of image and video identification and forgery detection. It encompasses both manipulated digital media and generative media. The paper is structured into two main sections: Section 3 focuses on image forensics, while Section 4 delves into video forensics. Each section covers detection methods (Sections 3.1, 3.2, 4.1, and 4.2), anti-forensics methods (Sections 3.3 and 4.3), as well as counter anti-forensics methods (Sections 3.4 and 4.4). The organization is visually represented in Figure 2. Additionally, the survey highlights some commonly used datasets in image and video forensics research . These datasets vary in size and contain a mix of real and fake images or videos for analysis. The objectives of this survey include providing an up-to-date review of state-of-the-art research in image and video forensics , examining generative images , analyzing anti-forensic strategies along with countermeasures . Furthermore, a comparison table is presented to showcase the coverage of various techniques across different surveys related to image and video forensics research. This comprehensive overview aims to shed light on the challenges faced in detecting manipulated digital media effectively while also paving the way for promising future directions in this field.