These are a selection of the most cited papers from ACM CCS, IEEE Security & Privacy, NDSS, Usenix Security, Crypto, and Eurocrypt between the years 2015 and 2019. Source data is from Google Scholar Metrics. The papers are roughly in the order of citations per year and grouped in 5…

Secure enclaves, or trusted execution environments (TEEs), generally describe small, trusted environments within a CPU that can execute code in a way that is not accessible by the normal operating system. Enclaves are a safe space to run code or process data in an otherwise untrusted environment. …

As part of the fellowship program at the Aspen Tech Policy Hub, I’ve spent several weeks with my colleagues Dr. Aloni Cohen and Dr. Amina Asim talking to people about how technology policy can better defend private enterprise from foreign nation-led cyberattacks. …

This posts talks about three security and privacy risks of machine learning models: poisoning attacks, evasion attacks, and unintended memorization. For an in-depth survey, see “A Marauder’s Map of Security and Privacy in Machine Learning”. Background on Machine Learning Models In an attempt to distill an entire field into a few sentences, machine learning generally…

Finding the origin of the “optimal radix” in classic computers — I was curious about the IOTA cryptocurrency citing radix economy as a justification for using ternary rather than binary circuits. I wanted to revisit the original assumptions in the computer science folklore that Euler’s number e is the “optimal radix”. The earliest reference I found on the subject was “High…

Inspired by “When Phone Encryption Blocks Justice” In June, a laptop was stolen from a bedroom on a Monday afternoon in Palo Alto, CA, a suburb 15 miles south of San Francisco. There were no witnesses to the larceny, and no surveillance footage either. With a laptop thief on the…