Publication: January-March 2026
Multimedia forensics plays a crucial role in investigating and combating cybercrime, especially in the context of digital images, videos, audio, and other media. With the proliferation of multimedia content and the increasing sophistication of cyber threats, there is a pressing need for innovative approaches that leverage Artificial Intelligence (AI) and Machine Learning (ML) techniques to enhance forensic investigations.
This special issue aims to bring together cutting-edge research at the intersection of AI, ML, and multimedia forensics, with a particular focus on detecting and analyzing multimedia-based cybercrime. We invite original contributions that address various aspects of AI and ML-enabled multimedia forensics, including but not limited to:
- Automated evidence extraction and analysis
- Evolving standards for AI and ML in multimedia forensics
- AI-based anomaly detection in multimedia forensics
- Deep learning techniques for multimedia forensics
- Privacy-preserving multimedia forensic investigations
- Forensic analysis of social media, cloud data and multisensory media
- Mobile device multimedia forensics and anti-forensic techniques
- Multimedia forensic investigation in IoT environments
- Ethical and legal implications of AI and ML in multimedia forensics
- The cultural impact of multimedia manipulation and forensics
Researchers and practitioners from academia, industry, and government agencies are invited to submit their original research contributions. Submitted papers should present novel ideas, theoretical insights, experimental results, or practical applications related to AI and ML-enabled digital forensics.
Important Dates:
- Paper Submission Deadline: Aug. 22, 2025
- Expected Publication: January-March 2026
Submission Guidelines
Authors are invited to submit original manuscripts via the
IEEE MultiMedia Author Portal site. Submitted papers must adhere to the
IEEE MultiMedia Submission Guidelines.
In addition to submitting your paper to
IEEE MultiMedia, you are also encouraged to upload the data related to your paper to
IEEE DataPort. IEEE DataPort is IEEE's data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission. Thank you!
Questions?
Contact the Lead Guest Editor at iyengar@cis.fiu.edu.
- Dr. S. S. Iyengar, Florida International University, USADirector, US Army funded Digital Forensics Center of Excellence, Distinguished University Professor
- Dr. Vir V. Phoha, Syracuse University, USAProfessor of Electrical Engineering & Computer Science (Biometrics, Cybersecurity, Machine Learning, Smart Phone and Tablet Security)
- Dr. Bhavani Thuraisingham, University of Texas, Dallas, USALouis A. Beecherl Jr. Distinguished Professor, Professor of Computer Science, Executive Director of the Cyber Security Research and Education Institute
We look forward to receiving your contributions and advancing the state-of-the-art in AI and ML-enabled multimedia forensics. 
