Adjunct Professor, Department of Computer Science
Adjunct Professor, Division of Health Informatics
2315 Stockton Blvd.
Sacramento, CA 95817
Dr. Peisert's current research and development interests cover a broad cross section of usable and useful computer security and privacy solutions, particularly in enabling secure and privacy-preserving scientific data analysis, improving security in high-performance computing systems, and power grid control systems. In the past, he has worked in areas including intrusion detection, computer forensics, insider threats, fault tolerance, vulnerability analysis and elections and electronic voting. Highlights of the R&D that he has led include inventing a means to identify misuse of high-performance and cloud computing systems, by identifying computation based on their communication patterns and power usage (now patented); inventing the idea of integrating network intrusion detection and safety engineering principles, leading to a system to detect cyber attacks against power distribution grid equipment by leveraging knowledge of the electrical physics of the system; and codification of the “Medical Science DMZ” notion — a network design pattern for extremely data-intensive, high-throughput data transfers, while remaining in compliance with security regulations such as HIPAA.
B.A., Computer Science, UC San Diego, La Jolla CA 1999
M.S., Computer Science, UC San Diego, San Diego CA 2000
Ph.D., Computer Science, UC San Diego, San Diego CA 2007
IEEE Technical Committee on Security and Privacy Outstanding Community Service Award, 2020
Senior Fellow, Berkeley Institute for Data Science (BIDS), 2018, 2019, 2020
JSCoRE 2014 Best Paper Award given by the U.S. Office of the Director of National Intelligence (ODNI), Director of Science and Technology, 2014
Institute for Information Infrastructure Protection (I3P) Fellow, 2007, 2008
SDSC Fellow, San Diego Supercomputer Center, UC San Diego, 2001, 2002, 2003, 2004, 2005, 2006, 2007
To view a detailed list of Dr. Peisert's publications, please click here.
Adams A, Avila K, Heymann E, Krenz M, Lee JR, Miller B, Peisert S. Guide to Securing Scientific Software. Trusted CI Report. 2021 Dec 14.
Ravi N, Scaglione A, Kadam S, Gentz R, Peisert S, Lunghino B, Levijarvi E, Shumavon A. Differentially Private K-means Clustering Applied to Meter Data Analysis and Synthesis. arXiv. 2021 Dec 7. arXiv:2112.03801.
Peisert S. Trustworthy Scientific Computing. Communications of the ACM (CACM). 2021 May;64(5):18-21. doi:10.1145/3457191.
Peisert S, Dart E, Barnett W, Balas E, Cuff J, Grossman RL, Berman A, Shankar A, Tierney B. The medical science DMZ: a network design pattern for data-intensive medical science. J Am Med Inform Assoc. 2018 Mar 1;25(3):267-274. doi:10.1093/jamia/ocx104. PMID:29040639.
Peisert S. Security in High-Performance Computing Environments. Communications of the ACM (CACM). 2017 Sep;60(9):72–80. doi:10.1145/3096742.
Peisert S. ASCR Cybersecurity for Scientific Computing Integrity. U.S. Department of Energy Office of Science report, Lawrence Berkeley National Laboratory (Report#:LBNL-6953E) 2015 Feb. doi:/10.2172/1223021.
McParland C, Peisert S, Scaglione A. Monitoring Security of Networked Control Systems: It’s the Physics. IEEE Security & Privacy. 2014 Nov/Dec;12(6):32–39. doi:10.1109/MSP.2014.122.
Akram A, Giannakou A, Akella V, Lowe-Power J, Peisert S. Performance Analysis of Scientific Computing Workloads on General Purpose TEEs. Proceedings of the 35th IEEE International Parallel & Distributed Processing Sysmposium (IPDPS). 2021 May.