Predicting function names in stripped binaries is an extremely useful but challenging task, as
it requires summarizing the execution behavior and semantics of the function in human …

Detecting semantically similar functions--a crucial analysis capability with broad real-world
security usages including vulnerability detection, malware lineage, and forensics--requires …

Binary code summarization, while invaluable for understanding code semantics, is
challenging due to its labor-intensive nature. This study delves into the potential of large …

Binary type inference is a critical reverse engineering task supporting many security
applications, including vulnerability analysis, binary hardening, forensics, and …

Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …

Software composition analysis (SCA) has attracted the attention of the industry and
academic community in recent years. Given a piece of program source code, SCA facilitates …

Detecting semantically similar binary functions–a crucial capability with broad security
usages including vulnerability detection, malware analysis, and forensics–requires …

Deep learning models are widely used in many applications. Despite their impressive
performance, the security aspect of these models has raised serious concerns. Universal …

Binary code representation learning has shown significant performance in binary analysis
tasks. But existing solutions often have poor transferability, particularly in few-shot and zero …

Static detection of security vulnerabilities in binary programs is an important research field in
software supply chain security. However, existing vulnerability detection methods based on …