2 citations · 5 across the 14 of their papers we have counts for
15 papers
Learning to Evade: Adaptive Attacks on Audio Watermarking
Weikang Ding, Hanqing Guo, Rui Duan +4
Advances in generative audio have intensified copyright concerns, making audio watermarking increasingly important for asserting ownership. However, existing audio watermarking met…
ClearMask: Noise-Free and Naturalness-Preserving Protection Against Voice Deepfake Attacks
Yuanda Wang, Bocheng Chen, Hanqing Guo +3
Voice deepfake attacks, which artificially impersonate human speech for malicious purposes, have emerged as a severe threat. Existing defenses typically inject noise into human spe…
SoK: How Robust is Audio Watermarking in Generative AI models?
Yizhu Wen, Ashwin Innuganti, Aaron Bien Ramos +2
Audio watermarking is increasingly used to verify the provenance of AI-generated content, enabling applications such as detecting AI-generated speech, protecting music IP, and defe…
DYNASHIELD: A Black-Box Moving Target Defense for LLMs via Dynamic Decoding Customization
Xiaoqun Liu, Weiming Qi, Qiben Yan
Large language models (LLMs) remain vulnerable to jailbreak attacks in which adversarial prompts induce harmful outputs. Existing defenses often require access to the model interna…
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…
The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs
Bocheng Chen, Hanqing Guo, Guangjing Wang +2
Large Language Models (LLMs) have demonstrated great capabilities in natural language understanding and generation, largely attributed to the intricate alignment process using huma…
A Practical Survey on Emerging Threats from AI-driven Voice Attacks: How Vulnerable are Commercial Voice Control Systems?
Yuanda Wang, Qiben Yan, Nikolay Ivanov +1
The emergence of Artificial Intelligence (AI)-driven audio attacks has revealed new security vulnerabilities in voice control systems. While researchers have introduced a multitude…
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…
Jailbreaker in Jail: Moving Target Defense for Large Language Models
Bocheng Chen, Advait Paliwal, Qiben Yan
Large language models (LLMs), known for their capability in understanding and following instructions, are vulnerable to adversarial attacks. Researchers have found that current com…
MASTERKEY: Practical Backdoor Attack Against Speaker Verification Systems
Hanqing Guo, Xun Chen, Junfeng Guo +2
Speaker Verification (SV) is widely deployed in mobile systems to authenticate legitimate users by using their voice traits. In this work, we propose a backdoor attack MASTERKEY, t…
PhantomSound: Black-Box, Query-Efficient Audio Adversarial Attack via Split-Second Phoneme Injection
Hanqing Guo, Guangjing Wang, Yuanda Wang +3
In this paper, we propose PhantomSound, a query-efficient black-box attack toward voice assistants. Existing black-box adversarial attacks on voice assistants either apply substitu…