• IEEE.org
  • IEEE CS Standards
  • Career Center
  • About Us
  • Subscribe to Newsletter

0

IEEE
CS Logo
  • MEMBERSHIP
  • CONFERENCES
  • PUBLICATIONS
  • EDUCATION & CAREER
  • VOLUNTEER
  • ABOUT
  • Join Us
CS Logo

0

IEEE Computer Society Logo
Sign up for our newsletter
FacebookTwitterLinkedInInstagramYoutube
IEEE COMPUTER SOCIETY
About UsBoard of GovernorsNewslettersPress RoomIEEE Support CenterContact Us
COMPUTING RESOURCES
Career CenterCourses & CertificationsWebinarsPodcastsTech NewsMembership
BUSINESS SOLUTIONS
Corporate PartnershipsConference Sponsorships & ExhibitsAdvertisingRecruitingDigital Library Institutional Subscriptions
DIGITAL LIBRARY
MagazinesJournalsConference ProceedingsVideo LibraryLibrarian Resources
COMMUNITY RESOURCES
GovernanceConference OrganizersAuthorsChaptersCommunities
POLICIES
PrivacyAccessibility StatementIEEE Nondiscrimination PolicyIEEE Ethics ReportingXML Sitemap

Copyright 2025 IEEE - All rights reserved. A public charity, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

  • Home
  • /Profiles
  • Home
  • /Profiles

Matt Bishop

Award Recipient

Featured ImageFeatured ImageMatt Bishop received his Ph.D. in computer science from Purdue University, where he specialized in computer security, in 1984. He was a research scientist at the Research Institute of Advanced Computer Science and on the faculty at Dartmouth College before joining the Department of Computer Science at the University of California at Davis in 1993.

His main research area is the analysis of vulnerabilities in computer systems, including modeling them, building tools to detect vulnerabilities, and ameliorating or eliminating them. He works in network security, resilience, attribution, data anonymization and sanitization, policy modeling, software assurance testing, and formal modeling of access control. He has worked on numerous analyses of e-voting systems including the RABA study in Maryland, and was one of the two principle investigators of the California Top-to-Bottom Review, which performed a technical review of all electronic voting systems certified in the State of California. With colleagues at the University of Massachusetts Amherst, he has applied process modeling to the election process as a whole.

He is active in the cybersecurity community. He was the founder of the USENIX UNIX Security Workshop and chaired the first one. It has since evolved into the USENIX Security Symposium, one of the premiere computer security conferences. He was a member of the California Voting Systems Technology Assessment Advisory Board. He provided technical advice to the California Assembly staff for the Electronic Recording Delivery Act of 2004 in California.

He is active in cybersecurity education. He co-led the Joint Task Force that developed the ACM/IEEE/ASIS SIGSAC/IFIP WG11.8 Cybersecurity Curricular Guidelines and the Summit on Education in Secure Software. His textbook, "Computer Security: Art and Science" is widely used in universities throughout the world; the second edition was published in November 2018 by Addison-Wesley Professional. He teaches introductory programming, operating systems, and computer security.

Awards

2022 Taylor L. Booth Education Award
“For contributions as an educator, author, and technical leader in cybersecurity education.”
Learn more about the Taylor L. Booth Award

LATEST NEWS
IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT
IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT
Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)
Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)
Autonomous Observability: AI Agents That Debug AI
Autonomous Observability: AI Agents That Debug AI
Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference
Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference
Copilot Ergonomics: UI Patterns that Reduce Cognitive Load
Copilot Ergonomics: UI Patterns that Reduce Cognitive Load
Get the latest news and technology trends for computing professionals with ComputingEdge
Sign up for our newsletter
Read Next

IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT

Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)

Autonomous Observability: AI Agents That Debug AI

Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference

Copilot Ergonomics: UI Patterns that Reduce Cognitive Load

The Myth of AI Neutrality in Search Algorithms

Gen AI and LLMs: Rebuilding Trust in a Synthetic Information Age

How AI Is Transforming Fraud Detection in Financial Transactions