Mark Scanlon
Biographic Data
| ID | 10397194 |
|---|---|
| NAME | Mark Scanlon |
| GIVEN NAMES | Mark |
| FAMILY NAME | Scanlon |
| SIGNATURE | SCANLON M |
| AFFILIATIONS | University College Dublin |
| ORCID | 0000-0002-6581-7164 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
AutoDFBench 1.0
The National Institute of Standards and Technology (NIST) Computer Forensic Tool Testing (CFTT) programme has become the de facto standard for providing digital forensic tool testing and validation. However to date, no comprehensive framework exists to automate benchmarking across the diverse forensic tasks included in the programme. This gap results in inconsistent validation, challenges in comparing tools, and limited validation reproducibility…
Vaas
Recent advances in AI-driven image generation have introduced new challenges for verifying the authenticity of digital evidence in forensic investigations. Modern generative models can produce visually consistent forgeries that evade traditional detectors based on pixel or compression artefacts. Most existing approaches also lack an explicit measure of anomaly intensity, which limits their ability to quantify the severity of manipulation. This pa…
Investigation of large language models, GenAI, and proprietary AI systems
Plug to place
Computer vision is a rapidly evolving field, giving rise to powerful new tools and techniques in digital forensic investigation, and shows great promise for novel digital forensic applications. One such application, indoor multimedia geolocation, has the potential to become a crucial aid for law enforcement in the fight against human trafficking, child exploitation, and other serious crimes. While outdoor multimedia geolocation has been widely ex…
No prominent works on this page.
AutoDFBench 1.0
The National Institute of Standards and Technology (NIST) Computer Forensic Tool Testing (CFTT) programme has become the de facto standard for providing digital forensic tool testing and validation. However to date, no comprehensive framework exists to automate benchmarking across the diverse forensic tasks included in the programme. This gap results in inconsistent validation, challenges in comparing tools, and limited validation reproducibility…
Vaas
Recent advances in AI-driven image generation have introduced new challenges for verifying the authenticity of digital evidence in forensic investigations. Modern generative models can produce visually consistent forgeries that evade traditional detectors based on pixel or compression artefacts. Most existing approaches also lack an explicit measure of anomaly intensity, which limits their ability to quantify the severity of manipulation. This pa…
Investigation of large language models, GenAI, and proprietary AI systems
Plug to place
Computer vision is a rapidly evolving field, giving rise to powerful new tools and techniques in digital forensic investigation, and shows great promise for novel digital forensic applications. One such application, indoor multimedia geolocation, has the potential to become a crucial aid for law enforcement in the fight against human trafficking, child exploitation, and other serious crimes. While outdoor multimedia geolocation has been widely ex…
Digital and Cyber Forensics (3 works) · Digital forensics (3 works) · Advanced Malware Detection Techniques (1 work) · Anomaly detection (1 work) · Augmented Reality Applications (1 work) · Authorship Attribution and Profiling (1 work) · Benchmarking (1 work) · Computer forensics (1 work) · Digital image (1 work) · Digital Media Forensic Detection (1 work)