Team 1 — AMLUCS

2026 Key Notes

Dr Emma Arakas

Behavioural Psychologist, Frazer Nash Consultancy

Emma has worked within secure government for over ten years, leading Behavioural Analytics and Insider Threat R&D programmes for the National Protective Security Authority (formerly the Centre for Protection of National Infrastructure [CPNI]). Emma is now a Principal Consultant working on the Psychology of AI, Socio-Cybersecurity, and Insider Threat.

A woman with short blonde hair wearing an orange sleeveless top and beige wide-leg pants, sitting on a beige bench, writing in a notebook with a gold pen, in a room with a large green plant and framed artwork in the background.

Professor Mark Herman

Professor of AI, University of Bristol

Keynote Speaker: Collaborative Intelligence for Cybersecurity

Andy Nicklin

Deputy Director for TF RAID, MOD

Hyrum Anderson

Hyrum Anderson is cofounder and CEO of Abundant Security. Previously, he was Senior Director of AI & Security at Cisco, via an acquisition of Robust Intelligence where he served as CTO. Much of his career has been focused on defense and security, having directed research projects at MIT Lincoln Laboratory, Sandia National Laboratories, Mandiant, as Chief Scientist at Endgame (acquired by Elastic), and Principal Architect of Trustworthy Machine Learning at Microsoft. While at Microsoft, he was the architect for Microsoft’s AI Red Team inaugural work on production AI systems as chair of the AI Red Team governing board. Hyrum co-founded the Conference on Applied Machine Learning in Information Security (CAMLIS), was appointed to serve on the 2024 National Academies study on Cyber Hard Problems, and has been an advisor to the US and UK governments on AI Safety and Security. He has spoken at numerous academic and industry conferences at the intersection of security and machine learning, including RSA, BlackHat and DEFCON. He has authored over 60 peer-reviewed academic publications, and co-authored the book Not With a Bug, But With a Sticker: Attacks on Machine Learning Systems and What To Do About Them. He received his PhD in Electrical Engineering from University of Washington, with an emphasis on signal processing and machine learning, and BS and MS degrees in Electrical Engineering from Brigham Young University.

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