5 papers
Making Sense of Scams: Understanding Scam Conversations Through Multi-Level Alignment
Zhenyu Mao, Jacky Keung, Xiangyu Li +4
Online scams often unfold gradually through interaction, yet existing detection systems predominantly rely on snapshot-based signals and interruptive warnings, revealing two resear…
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems
Jingyu Zhang, Jacky Wai Keung, Yan Xiao +3
Adversarial attacks play a pivotal role in testing and improving the reliability of deep learning (DL) systems. Existing literature has demonstrated that subtle perturbations to th…
Empirical Insights of Test Selection Metrics under Multiple Testing Objectives and Distribution Shifts
Jingyu Zhang, Fan Wang, Jacky Keung +3
Deep learning (DL)-based systems can exhibit unexpected behavior when exposed to out-of-distribution (OOD) scenarios, posing serious risks in safety-critical domains such as malwar…
Advancing Autonomous Driving System Testing: Demands, Challenges, and Future Directions
Yihan Liao, Jingyu Zhang, Jacky Keung +2
Autonomous driving systems (ADSs) promise improved transportation efficiency and safety, yet ensuring their reliability in complex real-world environments remains a critical challe…
FedLAD: A Modular and Adaptive Testbed for Federated Log Anomaly Detection
Yihan Liao, Jacky Keung, Zhenyu Mao +2
Log-based anomaly detection (LAD) is critical for ensuring the reliability of large-scale distributed systems. However, most existing LAD approaches assume centralized training, wh…