PhD Dissertation Proposal by YU Jiongchi | Towards Trustworthy and Secure Cloud-Native Ecosystems

Towards Trustworthy and Secure Cloud-Native Ecosystems

ABOUT THE TALK

Cloud-native computing has revolutionized the development, deployment, and scaling of modern software services. The ubiquitous adoption of containerization and its orchestration design has empowered cloud-native systems with unprecedented flexibility and agility, but has also introduced a broad attack surface and heightened reliability challenges, particularly as large organizations adopt increasingly complex cloud-native stacks.

This dissertation proposal addresses these challenges by advocating a vertically integrated perspective on cloud-native security and reliability. It includes three completed research works that span from (1) code-level inspection which focuses on bugs and testing of cloud native components, which uncover cloud-specific defect patterns and reveal that the majority of flaws evade existing test suites; (2) system-level cloud attack detection, focusing on the robustness of log-based attack detectors under realistic operational shifts and corresponding techniques for shift adaptation; and (3) organizational-level internal threat detection in cloud environments with incorporation of multi-agent framework for high-fidelity insider threat scenario simulations to enable adaptive internal protection. Together, these studies illuminate the groundwork toward building robust and secure cloud-native systems by embracing a comprehensive defense strategy.

SPEAKER BIOGRAPHY

Jiongchi Yu is a Ph.D. candidate at the SMU School of Computing and Information Systems, supervised by Prof. Xiaofei Xie. His research focuses on cloud-native system security and intelligent software engineering (AI4SE). His work has been published at top-tier conferences, including ICSE, FSE, ISSTA, WWW, and KDD. He is the recipient of SMU Presidential Doctoral Fellowship and the SCIS Dean's List Award.