[특강] Attack Surface Reduction through Software Debloating (6/13(화), 10:30)
- 융합보안대학원
- 조회수310
- 2023-05-30
■ Title: Attack Surface Reduction through Software Debloating
■ Abstract:
Memory safety vulnerabilities continue to be a major source of system compromise. While our efforts at hardening software have been effective, they are not enough. In this talk, I will show how removing unneeded code and features, referred to as debloating, can be used for software hardening. Software debloating is a promising technique for improving security without incurring any additional overhead. The main challenge in this area of work is to perform a sound analysis that does not mistakenly identify parts of the code that the program requires, as supplementary. While previous works have focused on reducing code at the userspace program level, I will show how we can achieve much better security guarantees by reducing the OS kernel features accessible by the program. Since userspace programs mainly leverage system calls to interact with the kernel, we will discuss how identifying and filtering the unneeded system calls of a userspace program allows us to neutralize previously disclosed Linux kernel vulnerabilities. I will conclude my talk by discussing how we can further reduce the attack surface by gradually transitioning to memory-safe languages.
■ Bio:
Seyedhamed Ghavamnia is an incoming Assistant Professor at the University of Connecticut. He received his Ph.D. from Stony Brook University where he was advised by Michalis Polychronakis. His research interests lie at the intersection of software security and programming languages. During his Ph.D., Seyedhamed has primarily focused on performing attack surface reduction through software debloating. He has published research papers in top security conferences, including IEEE Security and Privacy (S&P), Usenix Security Symposium, ACM CCS, and other prestigious conferences, such as RAID.
■ 강연일시 : 2023년 6월 13일(화) 10:30AM ~
■ 온라인 강의
Zoom링크 : https://us02web.zoom.us/j/89219459097?pwd=NnV3TTUzc3Vodno4TlptYzJlV1lQUT09