AI Forensics / FAIR-Lab
Research project focused on the robustness of AI-based tools in digital forensics, with attention to adversarial attacks, anti-forensic perturbations, OOD inputs, and operational reliability.
Selected technical and research-oriented projects in cybersecurity, digital forensics, OSINT, AI security, and external exposure assessment. The focus is on practical systems, applied research, and tools designed for investigation, monitoring, and risk triage.
Research project focused on the robustness of AI-based tools in digital forensics, with attention to adversarial attacks, anti-forensic perturbations, OOD inputs, and operational reliability.
Geospatial and event-based monitoring concept for OSINT collection, cyber-related event tracking, and external situational awareness.
Lightweight external exposure assessment for fast domain-level risk triage, including DNS, SSL/TLS, email security, and visible public-facing signals.
Experimental validation page for a documented external cyber risk screening format designed for vendor assessment, procurement, audit, and compliance support.
Technical work centered on forensic acquisition, investigative procedure, operational analysis, and evidence-oriented security workflows.
Ongoing work related to AI robustness, operational security evaluation, attack surface analysis, and practical monitoring systems.
Collection of lightweight web-based utilities for domain-level checks, token inspection, hashing, and DNS-oriented analysis.
Additional documentation will be expanded only when content is mature enough to be useful and consistent with the public portfolio.