Mark Scanlon Digital Forensics and Cybersecurity

Research

Research

Research themes spanning digital forensics, cybersecurity, applied AI, computer vision for investigations, cloud and IoT forensics, and forensic education.

Mark Scanlon’s research interests sit at the intersection of digital forensics, cybersecurity, and applied AI, developing and rigorously evaluating methods and tools that make digital evidence acquisition and analysis more efficient, automated, reliable, and reproducible.

The current research themes listed here are drawn from the existing personal site, publication record, and Forensics and Security Research Group profile.

Themes

Research Focus

Digital Forensics

Digital evidence acquisition and analysis methods that improve efficiency, reliability, automation, and reproducibility.

Cybersecurity

Security research connected to forensic readiness, cybercrime investigation, and practical investigative workflows.

AI for Forensics

Applied AI methods for evidence processing, investigation support, tool testing, and forensic workflow automation.

Computer Vision for Investigations

Computer vision approaches for digital forensic tasks including image analysis and investigative triage.

Cloud, IoT, and DFaaS

Research on cloud services, Internet of Things devices, Digital Forensics as a Service, and large-scale evidence handling.

Forensic Education

Teaching and curriculum activity in computer forensics, cybercrime investigation, and specialist digital investigation modules.

Related Output

Recent Publications

Full Publications List