34 citations · 83 across the 21 of their papers we have counts for
6 papers · 1 filter
Adversarial Agent Collaboration for Correctness Improvements of C to Safe Rust Translation
Tianyu Li, Ruishi Li, Bo Wang +3
Translating C to memory-safe languages, like Rust, prevents critical memory safety vulnerabilities that are prevalent in legacy C software. Even with recent LLM-based and tool-augm…
Securing Mixed Rust with Hardware Capabilities
Jason Zhijingcheng Yu, Fangqi Han, Kaustab Choudhury +2
The Rust programming language enforces three basic Rust principles, namely ownership, borrowing, and AXM (Aliasing Xor Mutability) to prevent security bugs such as memory safety vi…
A Practical and Secure Byzantine Robust Aggregator
De Zhang Lee, Aashish Kolluri, Prateek Saxena +1
In machine learning security, one is often faced with the problem of removing outliers from a given set of high-dimensional vectors when computing their average. For example, many…
Program Skeletons for Automated Program Translation
Bo Wang, Tianyu Li, Ruishi Li +2
Translating software between programming languages is a challenging task, for which automated techniques have been elusive and hard to scale up to larger programs. A key difficulty…
Anvil: A General-Purpose Timing-Safe Hardware Description Language
Jason Zhijingcheng Yu, Aditya Ranjan Jha, Umang Mathur +2
Expressing hardware designs using hardware description languages (HDLs) routinely involves using stateless signals whose values change according to their underlying registers. Unin…
Model Provenance Testing for Large Language Models
Ivica Nikolic, Teodora Baluta, Prateek Saxena
Large language models are increasingly customized through fine-tuning and other adaptations, creating challenges in enforcing licensing terms and managing downstream impacts. Track…