## 3 Related Work and Literature Review
### Emerging Trends in Forensic Watermarking  
Some studies propose forensic watermarking techniques to detect and authenticate digital media tampering. However, gaps remain in the broader applicability of these techniques in real-world investigative contexts. [PERSON] and [PERSON] [16] propose a watermarking scheme for digital rights management for mobile Internet forensics. Their method embeds user and device information as a robust watermark for source identification. They incorporate image features as a semi-fragile watermark for tamper detection. Their results demonstrate robustness against various attacks. However, the study limits its scope to image data from mobile devices. They fail to extend their utility to broader forensic applications, particularly in contexts where forensic evidence spans various types of digital media such as disk images or document files. [PERSON] and [PERSON] [10] conducted a review on digital watermarking methods for image forensics. The authors compared fragile methods and highlighted the advantages of active forensic methods over passive ones and noted improvements in accuracy and computational efficiency. However, the review neglects key forensic considerations. They did not address the investigative context or post-acquisition evidence protection, such as ensuring the integrity of evidence during collection and transfer. [PERSON] et al. [57] proposed a rate-distortion-preserving forensic watermarking technique for video data. Their method preserves the quality and compression efficiency of video files and embeds watermarks during video encoding. However, this approach constrains itself to video data. They did not address the complexities involved in maintaining the integrity of forensic disk images, particularly those containing various file types. [PERSON] et al. [58] introduce an intelligent text watermarking technique (ANiTW) for forensic identification on social media. The scheme embeds invisible watermarks in text-based data and uses machine learning to detect and quantify manipulation. This method proves effective in verifying content integrity and authorship on platforms where text manipulation occurs frequently. However, the study focusses narrowly on text data. [PERSON] et al. [59] propose a digital audio encryption and forensic watermarking scheme to improve the privacy and security of audio signals. Their technique embeds watermarks in encrypted audio data. This allows for tamper detection and content authentication even when audio storage occurs in third-party cloud environments. Although this study marks significant progress in the security of digital audio content, it lacks generalisability to other forms of forensic evidence, such as disk images. These studies highlight the growing importance of forensic watermarking in different media types. However, they collectively fail to address several important forensic requirements. None of the reviewed works apply watermarking in the context of a forensic investigation. The focus primarily lies on pre-emptive or post hoc tamper detection and authentication measures for specific media types. This approach neglects the broader context of digital evidence collection, transfer, and preservation. Critical chain-of-custody issues, fundamental to evidence admissibility in legal proceedings, receive no attention. Furthermore, none of these studies demonstrate integration with standard forensic analysis tools, which creates a significant obstacle to practical adoption in actual investigations.