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Michael Dixon
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Research Scientist, Cryptographer, and Cyber Security Engineer
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About
I am a computer scientist and researcher focusing on cyber security, cryptography, formal methods, and national security. I am currently a Senior Cyber Security Research Scientist and Principal Investigator in the Advanced Research in Cyber Systems (A-4) group at Los Alamos National Laboratory. I lead laboratory efforts in cryptography and formal methods research.
My research portfolio encompasses over $19 million in funding as PI or co-PI.
Primary Research Areas of Interest:
- Advanced Cryptography: Zero-knowledge Proofs, Secure Multi-party Computation, Fully Homomorphic Encryption, Obfuscation
- Artificial Intelligence Security: Assurance, Arms Control, Verification, Deepfake Detection, Adversarial Robustness
- Formal Verification: Cryptographic Protocol Verification, Provable System Security, SAT/SMT Solvers
- Cyber Physical Security: Anti-tamper, Physical Unclonable Functions
Email: Click to Request
Profiles: Linkedin StackExchange
Education:
- Massachusetts Institute of Technology
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| Advanced Study Program Fellowship |
2018 |
| Course 6: Electrical Engineering and Computer Science |
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- University of Michigan, College of Engineering
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| B.S.E in Computer Science Engineering |
2016 |
| Minor in Mathematics |
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Recent Work & Research Experience:
- Los Alamos National Laboratory, Los Alamos, NM
| Senior Cyber Security Research Scientist |
2019 - Present |
- Charles Stark Draper Laboratory, Cambridge, MA
| Cyber Security Research & Development Engineer |
2017 - 2019 |
Massachusetts Institute of Technology, Cambridge, MA
| Undergraduate Researcher |
2012 |
The MITRE Corporation, McLean, VA & Ft. Meade, MD-
| Cyber Security Research Intern |
2009 - 2010 |
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Publications:
- Learnability of Optical Physical Unclonable Functions through the Lens of Learning with Errors
- Pending Publication
- Apollo Albright, Boris Gelfand, Michael Dixon
- [PDF] [ArXiV]
- zkQMC: Zero-Knowledge Proofs For (Some) Probabilistic Computations Using Quasi-Randomness
- IACR ePrint Archive
Zachary DeStefano, Dani Barrack, Michael Dixon
- [PDF] [IACR]
- Using Binary Analysis Frameworks: The Case for BAP and angr
NASA Formal Methods 2019
Chris Casinghino, J. T. Paasch, Cody Roux, John Altidor, Michael Dixon & Dustin Jamner
[PDF] [Publisher]
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