The arms race between Internet freedom advocates and censors has catalyzed the emergence of sophisticated blockingtechniques and directed significant research emphasis toward the development of automated censorship measurement and evasion tools based …
The arms race between Internet freedom technologists and censoring regimes has catalyzed the deployment of more sophisticated censoring techniques and directed significant research emphasis toward the development of automated tools for censorship …
The widespread usage of machine learning (ML) in a myriad of domains has raised questions about its trustworthiness in security-critical environments. Part of the quest for trustworthy ML is robustness evaluation of ML models to test-time adversarial …
Robustness to adversarial examples of machine learning models remains an open topic of research. Attacks often succeed by repeatedly probing a fixed target model with adversarial examples purposely crafted to fool it. In this paper, we introduce …
Machine Learning (ML) models are susceptible to evasion attacks. Evasion accuracy is typically assessed using aggregate evasion rate, and it is an open question whether aggregate evasion rate enables feature-level diagnosis on the effect of …
Modern Code review is one of the most critical tasks in software maintenance and evolution. A rigorous code review leads to fewer bugs and reduced overall maintenance costs. Most existing studies focus on automatically identifying the most qualified …