The Berkeley Lab’s Computational Research Division is an active participant in a number of projects in the arena of security for scientific, high-performance computing systems and high-bandwidth research and education networks. Research sponsors have typically included DOE’s ASCR program and the National Science Foundation (NSF) SaTC program and OAC office, among others.
LBNL’s cybersecurity goals are to research, develop, evaluate, adapt, and integrate advanced security and privacy solutions that enable or improve scientific workflows that may otherwise not be possible due to real or perceived security restrictions that, using today’s solution, impose onerous usability and/or performance constraints, thereby hindering scientific progress.
LBNL has had a leadership role in security in scientific computing environments for many years, including the development of the Zeek (Bro) Network Security Monitor, the 100G performance enhancements of Zeek (Bro), and Zeek (Bro)’s commercial spin-off, Corelight, Inc., as well as leading several DOE-sponsored activities related to defining a cybersecurity research program within the DOE Office of Science. More recently, LBNL led the coordination of the “Cyber R&D” Enterprise Cyber Capability (ECC) of the DOE-wide Integrated Joint Cybersecurity Coordination Center (iJC3) — a sponsored R&D program involving ten DOE National Laboratories as performers. LBNL is currently a co-lead of Trusted CI, the NSF Cybersecurity Center of Excellence.
Recent highlights of LBNL’s cybersecurity R&D activities include:
Development of a research roadmap for co-designing high-performance computing systems with security built in.
Development of the Medical Science DMZ design pattern as a method that allows data flows at scale while simultaneously addressing the HIPAA Security Rule and related regulations governing biomedical data and appropriately managing risk.
ASCR Cybersecurity for Scientific Computing Workshop, June 2–3, 2015 [ report]
DOE Cybersecurity R&D Challenges for Open Science: Developing a Roadmap and Vision, January 24–26, 2007 [ news, report]
Summer Students Tackle COVID-19 — Oct. 21, 2020
Into the Medical Science DMZ (Science Node) — March 23, 2018
Berkeley Lab Researchers Contribute to Making Blockchains Even More Robust — January 30, 2018
Mind the gap: Speaking like a cybersecurity pro — Feb. 10, 2017
Building a CENIC Security Strategy — Jan. 11, 2017
Ayaz Akram, Anna Giannakou, Venkatesh Akella, Jason Lowe-Power, and Sean Peisert, “ Performance Analysis of Scientific Computing Workloads on General Purpose TEEs,” Proceedings of the 35th IEEE International Parallel & Distributed Processing Sysmposium (IPDPS), May 17–21, 2021.
Ayaz Akram, Anna Giannakou, Venkatesh Akella, Jason Lowe-Power, and Sean Peisert, “ Performance Analysis of Scientific Computing Workloads on Trusted Execution Environments,” arXiv preprint arXiv:2010.13216, 25 Oct 2020.
Bogdan Copos and Sean Peisert, “ Catch Me If You Can: Using Power Analysis to Identify HPC Activity,” arXiv preprint arXiv:2005.03135, 2020.
Sean Peisert, Eli Dart, William K. Barnett, James Cuff, Robert L. Grossman, Edward Balas, Ari Berman, Anurag Shankar, and Brian Tierney, “ The Medical Science DMZ: An Network Design Pattern for Data-Intensive Medical Science”, Journal of the American Medical Informatics Association (JAMIA), 25,(3):267–274, March 2018.
Sean Peisert, “ Security in High-Performance Computing Environments”, Communications of the ACM (CACM), 60(9):72-80, September 2017.
Sean Peisert, Von Welch, Andrew Adams, Michael Dopheide, Susan Sons, RuthAnne Bevier, Rich LeDuc, Pascal Meunier, Stephen Schwab, and Karen Stocks, Ilkay Altintas, James Cuff, Reagan Moore, and Warren Raquel, “ Open Science Cyber Risk Profile,” February 2017.
Sean Whalen, Sean Peisert, Matt Bishop, “ Multiclass Classification of Distributed Memory Parallel Computations,” Pattern Recognition Letters (PRL), 34(3):322-329, February 2013.
Sean Whalen, Sophie Engle, Sean Peisert, Matt Bishop, “ Network-Theoretic Classification of Parallel Computation Patterns,” International Journal of High Performance Computing Applications (IJHPCA), 26(2):159-169, May 2012.