1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
Automated Repair of TEE Partitioning Issues via DSL-Guided and LLM-Assisted Patching
Chengyan Ma, Jieke Shi, Ruidong Han +4
Trusted Execution Environments (TEEs) provide hardware-based isolation to protect sensitive data and computations from potentially compromised operating systems (OS). However, TEE…
Finding Missing Input Validation in TEEs via LLM-Assisted Symbolic Execution
Chengyan Ma, Jieke Shi, Ruidong Han +3
Trusted Execution Environments (TEEs) provide hardware-enforced isolation that protects sensitive code and data from untrusted software. Despite their strong security guarantees, a…
AgentSZZ: Teaching the LLM Agent to Play Detective with Bug-Inducing Commits
Yunbo Lyu, Jieke Shi, Hong Jin Kang +8
The SZZ algorithm is the dominant technique for identifying bug-inducing commits and underpins many software engineering tasks, such as defect prediction and vulnerability analysis…
What You Trust Is Insecure: Demystifying How Developers (Mis)Use Trusted Execution Environments in Practice
Yuqing Niu, Jieke Shi, Ruidong Han +4
Trusted Execution Environments (TEEs), such as Intel SGX and ARM TrustZone, provide isolated regions of CPU and memory for secure computation and are increasingly used to protect s…
Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learning
Ye Liu, Yuqing Niu, Chengyan Ma +5
Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging beca…