Software Security

Software security research aims to improve the resilience of software systems against vulnerabilities and attacks. Current efforts focus on automated vulnerability detection using machine learning models, including graph neural networks and large language models (LLMs), to analyze code and identify potential weaknesses, as well as on enhancing user interfaces to improve security without sacrificing usability. These advancements are crucial for mitigating the ever-growing threat of software exploits and improving the overall security posture of software systems, impacting both the development process and the safety of users.