Democratizing Health Research Through Privacy-Protecting Synthetic Data

This project aims to enable significantly broader use of health data by creating differentially private synthetic data sets. This project will also contribute to solutions for the focus on the coronavirus pandemic. It is supported by the UC Davis CeDAR.

Privacy-Preserving Data Analysis for Scientific Discovery

This project aims to produce methods, processes, and architectures applicable to a variety of scientific computing domains that enables querying, machine learning, and analysis of data while protecting against releasing sensitive information beyond pre-defined bounds. It is supported by LBNL CSR funds and is led by Sean Peisert.

Trusted CI — the National Science Foundation Cybersecurity of Excellence

The mission of Trusted CI is to improve the cybersecurity of NSF computational science and engineering projects, while allowing those projects to focus on their science endeavors. The PI of this center at Indiana University is Von Welch. LBNL’s role in this center is led by Sean Peisert.

Medical Science DMZ

We have defined a Medical Science DMZ 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.

Detecting Distributed Denial of Service Attacks on Wide-Area Networks

This project develops techniques for detecting DDoS attacks and disambiguating them from large-scale science flows. It is funded by the DOE iJC3 Cyber R&D program and is led by Sean Peisert.

Toward a Hardware/Software Co-Design Framework for Ensuring the Integrity of Exascale Scientific Data

This project takes a broad look at several aspects of security and scientific integrity issues in HPC systems. It is funded by DOE ASCR and is led by Sean Peisert.

Inferring Computing Activity Using Physical Sensors

This project uses power data to monitor the use of computing systems, including supercomputers and large computing centers. It is led by Sean Peisert.

Host and Network Resilience

This project focused on mapping and analyzing the qualities of resilient networks by investigating components of redundancy, diversity, quality of service, etc… The project’s goal is to be able to quantify and compare the resilience of networks in a scientifically meaningful way. This project was led at LBNL by Sean Peisert.

A Mathematical and Data-Driven Approach to Intrusion Detection for High-Performance Computing

This project developed mathematical and statistical techniques to analyze the secure access and use of high-performance computer systems. It was funded by DOE ASCR and was originally led by David H. Bailey.

I3P Data Sanitization

This project looked at defining means for understanding what data can be sanitized, and how. At LBNL, this project was led by Sean Peisert and was funded by the Institute for Information Infrastructure Protection (I3P).