10 papers
Mostly Automatic Translation of Language Interpreters from C to Safe Rust
Bo Wang, Brandon Paulsen, Joey Dodds +3
Translating C programs to safe Rust is challenging owing to significant differences in typing constraints, ownership, and borrowing rules. Interpreter programs are particularly imp…
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…
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…
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…
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…
CLUE-MARK: Watermarking Diffusion Models using CLWE
Kareem Shehata, Aashish Kolluri, Prateek Saxena
As AI-generated images become widespread, reliable watermarking is essential for content verification, copyright enforcement, and combating disinformation. Existing techniques rely…