Muhammad Mudassar Yamin
Associate Professor
Norwegian University of Science and Technolgy
Dr. Muhammad Mudassar Yamin is currently an Associate Professor in the Department of Information and Communication Technology at the Norwegian University of Science and Technology (NTNU). His research focuses on system security, penetration testing, security assessment, and intrusion detection.Dr. Yamin’s contributions to cybersecurity have been recognized by over 50 Fortune 500 companies. He has received an Innovation Medal from INTERPOL and appreciation letters from the French military and Pakistan counter terrorism department for his work. He also holds several professional cybersecurity certifications, including OSCE, OSCP, LPT-MASTER, CEH, CHFI, CPTE, CISSO, and CBP.
Speaker sessions
Briefings and Arsenals | Confirmed Speakers | No Session Assigned
Placeholder session for confirmed speakers without an assigned session, allowing them to be pushed to Swapcard and Visit.
- 07:30
- Tue
- 01 Dec
Stage:
Briefing Stage 2
Sessions Type:
Keynote
Still Something to Teach: Undergrad Ethical Hacking Tasks That Publicly Available AI Still Struggles With
The rapid proliferation of publicly available generative AI tools has created a fundamental pedagogical challenge in cybersecurity education. Students can increasingly delegate ethical hacking tasks, including reconnaissance, exploitation, and binary analysis to AI assistants, undermining the diagnostic validity of traditional assessments. The present study investigates the extent to which current AI systems can solve undergraduate-level penetration testing tasks and proposes evidence-based design strategies to preserve the assessment integrity. Drawing on empirical data from NTNU's IIK3100 Ethical Hacking and Penetration Testing course, the researchers have analysed 99,801 submissions from 563 students who were granted unrestricted access to publicly available AI tools across 55 Capture-the-Flag (CTF) challenges. The analysis has identified four design principles(1) deceptive information,(2) contextual intuition, (3) mandatory manual analysis, and (4) chained multi-step reasoning, that consistently resisted AI automation while remaining solvable by human learners with foundational competencies. The findings have provided actionable recommendations for reconstructing cybersecurity curricula to maintain educational rigour while preparing graduates for an AI-augmented professional environment.
- 13:30
- Thu
- 03 Dec
Stage:
Briefing Stage 1
Sessions Type:
Keynote