Leveraging deep learning techniques to secure software development - Siow, Jing Kai (Nanyang Technological University, 2022)
Adversarial threats have grown rapidly in recent years, resulting in the growing importance of software security. Many processes in the software development life cycle seek to reduce attack surfaces in the codebase, e.g., black box testing, code reviews, and static code analysis. The key idea is to reduce implementation bugs, such as out-of-bounds bugs and memory leaks, during the development phase. However, they often require an intensive amount of resources, further reducing the productivity of developers. Therefore, automation in software development processes is highly sought.