Shouling Ji

Remote Attacks on Drones Vision Sensors: An Empirical Study

2021 · IEEE Transactions on Dependable and Secure Computing

Vision systems applied to drones, automatic vehicles, and robots have become an increasingly popular sensing method. However, vision sensors that make up these systems are vulnerable to malicious input attacks, which can lead to serious …

Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion

2021 · arXiv (Cornell University)

Smart contracts hold digital coins worth billions of dollars, their security issues have drawn extensive attention in the past years. Towards smart contract vulnerability detection, conventional methods heavily rely on fixed expert rules, leading to …

SyzTrust: State-aware Fuzzing on Trusted OS Designed for IoT Devices

2023 · arXiv (Cornell University)

Trusted Execution Environments (TEEs) embedded in IoT devices provide a deployable solution to secure IoT applications at the hardware level. By design, in TEEs, the Trusted Operating System (Trusted OS) is the primary component. It …

AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection

2023 · arXiv (Cornell University)

Code Clone Detection, which aims to retrieve functionally similar programs from large code bases, has been attracting increasing attention. Modern software often involves a diverse range of programming languages. However, current code clone detection methods …

TREC: APT Tactic / Technique Recognition via Few-Shot Provenance Subgraph Learning

2024

APT (Advanced Persistent Threat) with the characteristics of persistence, stealth, and diversity is one of the greatest threats against cyber-infrastructure. As a countermeasure, existing studies leverage provenance graphs to capture the complex relations between system …