Inferring Computing Activity Using Physical Sensors
Sean Peisert (PI)
Bogdan Copos (LBNL/UC Davis; Ph.D. 2017) → SRI International → Google
This project involves using power data for monitoring use of computing systems, including supercomputers and large computing centers. By using power data, as opposed to data provided by the computing environment itself, the technology collects the data non-invasively. More information is available at the LBNL Innovation and Partnerships Office.
Publications resulting from this project:
Bogdan Copos and Sean Peisert, “Catch Me If You Can: Using Power Analysis to Identify HPC Activity,” arXiv preprint arXiv:2005.03135, 2020.
Melissa Stockman, Dipankar Dwivedi, Reinhard Gentz, Sean Peisert, “Detecting Programmable Logic Controller Code Using Machine Learning” International Journal of Critical Infrastructure Protection, accepted July 3, 2019. [DOI]
Bogdan Copos, Sean Peisert (advisor), Modeling Systems Using Side Channel Information. PhD dissertation, University of California, Davis, 2017.
More information is available on other LBNL R&D projects focusing on cybersecurity in general, as well as specifically on HPC Security projects.
Software resulting from this project:
Identifying Computational Operations Based on Power Measurements
More information is available on other Berkeley Lab R&D projects focusing on cybersecurity in general, as well as specifically on cybersecurity for scientific and high-performance computing.