16 citations · 53 across the 16 of their papers we have counts for
17 papers
Kill Two Birds with One Stone! Trajectory enabled Unified Online Detection of Adversarial Examples and Backdoor Attacks
Anmin Fu, Fanyu Meng, Huaibing Peng +5
The proposed UniGuard is the first unified online detection framework capable of simultaneously addressing adversarial examples and backdoor attacks. UniGuard builds upon two key i…
From Pixels to Trajectory: Universal Adversarial Example Detection via Temporal Imprints
Yansong Gao, Huaibing Peng, Hua Ma +5
For the first time, we unveil discernible temporal (or historical) trajectory imprints resulting from adversarial example (AE) attacks. Standing in contrast to existing studies all…
Comprehensive Evaluation of Cloaking Backdoor Attacks on Object Detector in Real-World
Hua Ma, Alsharif Abuadbba, Yansong Gao +2
The exploration of backdoor vulnerabilities in object detectors, particularly in real-world scenarios, remains limited. A significant challenge lies in the absence of a natural phy…
Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense
Hua Ma, Shang Wang, Yansong Gao +7
All current backdoor attacks on deep learning (DL) models fall under the category of a vertical class backdoor (VCB) -- class-dependent. In VCB attacks, any sample from a class act…
DeepTheft: Stealing DNN Model Architectures through Power Side Channel
Yansong Gao, Huming Qiu, Zhi Zhang +6
Deep Neural Network (DNN) models are often deployed in resource-sharing clouds as Machine Learning as a Service (MLaaS) to provide inference services.To steal model architectures t…
One-to-Multiple Clean-Label Image Camouflage (OmClic) based Backdoor Attack on Deep Learning
Guohong Wang, Hua Ma, Yansong Gao +6
Image camouflage has been utilized to create clean-label poisoned images for implanting backdoor into a DL model. But there exists a crucial limitation that one attack/poisoned ima…
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Qun Li, Chandra Thapa, Lawrence Ong +5
Federated learning (FL) is the most popular distributed machine learning technique. FL allows machine-learning models to be trained without acquiring raw data to a single point for…
TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World
Hua Ma, Yinshan Li, Yansong Gao +6
Object detection is the foundation of various critical computer-vision tasks such as segmentation, object tracking, and event detection. To train an object detector with satisfacto…
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning
Hua Ma, Qun Li, Yifeng Zheng +5
Federated Learning (FL), a distributed machine learning paradigm, has been adapted to mitigate privacy concerns for customers. Despite their appeal, there are various inference att…
Towards A Critical Evaluation of Robustness for Deep Learning Backdoor Countermeasures
Huming Qiu, Hua Ma, Zhi Zhang +4
Since Deep Learning (DL) backdoor attacks have been revealed as one of the most insidious adversarial attacks, a number of countermeasures have been developed with certain assumpti…
Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World
Hua Ma, Yinshan Li, Yansong Gao +7
Deep learning models have been shown to be vulnerable to recent backdoor attacks. A backdoored model behaves normally for inputs containing no attacker-secretly-chosen trigger and…
NTD: Non-Transferability Enabled Backdoor Detection
Yinshan Li, Hua Ma, Zhi Zhang +6
A backdoor deep learning (DL) model behaves normally upon clean inputs but misbehaves upon trigger inputs as the backdoor attacker desires, posing severe consequences to DL model d…
Quantization Backdoors to Deep Learning Commercial Frameworks
Hua Ma, Huming Qiu, Yansong Gao +7
Currently, there is a burgeoning demand for deploying deep learning (DL) models on ubiquitous edge Internet of Things (IoT) devices attributed to their low latency and high privacy…
RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things
Huming Qiu, Hua Ma, Zhi Zhang +6
Though deep neural network models exhibit outstanding performance for various applications, their large model size and extensive floating-point operations render deployment on mobi…
Detecting Recycled Commodity SoCs: Exploiting Aging-Induced SRAM PUF Unreliability
Yansong Gao, Hua Ma, Said F. Al-Sarawi +2
A physical unclonable function (PUF), analogous to a human fingerprint, has gained an enormous amount of attention from both academia and industry. SRAM PUF is among one of the pop…
Exploiting PUF Models for Error Free Response Generation
Yansong Gao, Hua Ma, Geifei Li +5
Physical unclonable functions (PUF) extract secrets from randomness inherent in manufacturing processes. PUFs are utilized for basic cryptographic tasks such as authentication and…
PUF-FSM: A Controlled Strong PUF
Yansong Gao, Damith C. Ranasinghe
This paper presents the PUF finite state machine (PUF-FSM) that is served as a practical {\it controlled} strong PUF. Previous controlled PUF designs have the difficulties of stabi…