1 citations · 1 across the 8 of their papers we have counts for
8 papers
Null-Space Constrained Low-Rank Adaptation for Response-Specified Large Language Model Unlearning
Bocheng Ju, Jianhua Wang, Chengliang Liu +1
Large language model unlearning aims to suppress designated undesirable knowledge while preserving benign capabilities. Many unlearning objectives focus on suppressing undesired an…
Sparse Threats, Focused Defense: Criticality-Aware Robust Reinforcement Learning for Safe Autonomous Driving
Qi Wei, Junchao Fan, Zhao Yang +3
Reinforcement learning (RL) has shown considerable potential in autonomous driving (AD), yet its vulnerability to perturbations remains a critical barrier to real-world deployment.…
Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach
Junchao Fan, Qi Wei, Ruichen Zhang +4
Deep reinforcement learning (DRL) has demonstrated remarkable success in developing autonomous driving policies. However, its vulnerability to adversarial attacks remains a critica…
PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning
Jianhua Wang, Xiaolin Chang, Jelena Mišić +3
Recently, big data has seen explosive growth in the Internet of Things (IoT). Multi-layer FL (MFL) based on cloud-edge-end architecture can promote model training efficiency and mo…
Towards Runtime Customizable Trusted Execution Environment on FPGA-SoC
Yanling Wang, Xiaolin Chang, Haoran Zhu +3
Processing sensitive data and deploying well-designed Intellectual Property (IP) cores on remote Field Programmable Gate Array (FPGA) are prone to private data leakage and IP theft…
CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning
Jianhua Wang, Xiaolin Chang, Jelena Mišić +3
Federated Learning (FL), a privacy-oriented distributed ML paradigm, is being gaining great interest in Internet of Things because of its capability to protect participants data pr…
Practical Solutions in Fully Homomorphic Encryption -- A Survey Analyzing Existing Acceleration Methods
Yanwei Gong, Xiaolin Chang, Jelena Mišić +3
Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread application in various fields, like outso…
DI-AA: An Interpretable White-box Attack for Fooling Deep Neural Networks
Yixiang Wang, Jiqiang Liu, Xiaolin Chang +2
White-box Adversarial Example (AE) attacks towards Deep Neural Networks (DNNs) have a more powerful destructive capacity than black-box AE attacks in the fields of AE strategies. H…