156 citations · 168 across the 8 of their papers we have counts for
12 papers
Can Autonomous Vehicles Keep Their Cool? A Survey of Thermal Side-Channel and Perception Attacks
Harsh Aaryan, Ce Zhou
Autonomous vehicles (AVs) couple safety-critical perception to thermally constrained compute. Interfaces built for night perception and package thermal reliability were never engin…
Adversarial Robustness of Camera-Radar Sensor Fusion for Autonomous Driving
Ce Zhou, Yubo Wu, Khang Nguyen +3
Autonomous driving (AD) relies on multi-sensor perception to interpret the surrounding environment. However, the robustness of camera--radar fusion under adversarial conditions rem…
Can You Trust What You See? Alpha Channel No-Box Attacks on Video Object Detection
Ariana Yi, Ce Zhou, Liyang Xiao +1
As object detection models are increasingly deployed in cyber-physical systems such as autonomous vehicles (AVs) and surveillance platforms, ensuring their security against adversa…
Optical Lens Attack on Monocular Depth Estimation for Autonomous Driving
Ce Zhou, Qiben Yan, Daniel Kent +4
Monocular Depth Estimation (MDE) is a pivotal component of vision-based Autonomous Driving (AD) systems, enabling vehicles to estimate the depth of surrounding objects using a sing…
Decoding Emotions: Unveiling Facial Expressions through Acoustic Sensing with Contrastive Attention
Guangjing Wang, Juexing Wang, Ce Zhou +4
Expression recognition holds great promise for applications such as content recommendation and mental healthcare by accurately detecting users' emotional states. Traditional method…
Transient Adversarial 3D Projection Attacks on Object Detection in Autonomous Driving
Ce Zhou, Qiben Yan, Sijia Liu
Object detection is a crucial task in autonomous driving. While existing research has proposed various attacks on object detection, such as those using adversarial patches or stick…
Optical Lens Attack on Deep Learning Based Monocular Depth Estimation
Ce Zhou, Qiben Yan, Daniel Kent +3
Monocular Depth Estimation (MDE) plays a crucial role in vision-based Autonomous Driving (AD) systems. It utilizes a single-camera image to determine the depth of objects, facilita…
Protecting Activity Sensing Data Privacy Using Hierarchical Information Dissociation
Guangjing Wang, Hanqing Guo, Yuanda Wang +3
Smartphones and wearable devices have been integrated into our daily lives, offering personalized services. However, many apps become overprivileged as their collected sensing data…
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems
Guangjing Wang, Ce Zhou, Yuanda Wang +3
Transferable attacks allow adversarial manipulations or learned attack mechanisms constructed in one setting to compromise other AI systems, potentially reducing attack costs and a…
ChargeX: Exploring State Switching Attack on Electric Vehicle Charging Systems
Ce Zhou, Qiben Yan, Zhiyuan Yu +4
Electric Vehicle (EV) has become one of the promising solutions to the ever-evolving environmental and energy crisis. The key to the wide adoption of EVs is a pervasive charging in…
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
Ce Zhou, Qian Li, Chen Li +16
Pretrained Foundation Models (PFMs) are regarded as the foundation for various downstream tasks with different data modalities. A PFM (e.g., BERT, ChatGPT, and GPT-4) is trained on…
DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems
Ce Zhou, Qiben Yan, Yan Shi +1
Depth estimation-based obstacle avoidance has been widely adopted by autonomous systems (drones and vehicles) for safety purpose. It normally relies on a stereo camera to automatic…