175 citations · 562 across the 37 of their papers we have counts for
40 papers
Robust Estimation of Sparse Numerical Vectors under Local Differential Privacy
Puning Zhao, Zhikun Zhang, Shaowei Wang +5
Local differential privacy (LDP) protocols are vulnerable to poisoning attacks. Existing research have proposed efficient defense strategies for single-item users. However, in prac…
KUDA: Knowledge Unlearning by Deviating Representation for Large Language Models
Ce Fang, Zhikun Zhang, Min Chen +4
Large language models (LLMs) acquire a large amount of knowledge through pre-training on vast and diverse corpora. While this endows LLMs with strong capabilities in generation and…
DWBench: Holistic Evaluation of Watermark for Dataset Copyright Auditing
Xiao Ren, Xinyi Yu, Linkang Du +5
The surging demand for large-scale datasets in deep learning has heightened the need for effective copyright protection, given the risks of unauthorized use to data owners. Althoug…
PrivATE: Differentially Private Average Treatment Effect Estimation for Observational Data
Quan Yuan, Xiaochen Li, Linkang Du +6
Causal inference plays a crucial role in scientific research across multiple disciplines. Estimating causal effects, particularly the average treatment effect (ATE), from observati…
VICTOR: Dataset Copyright Auditing in Video Recognition Systems
Quan Yuan, Zhikun Zhang, Linkang Du +5
Video recognition systems are increasingly being deployed in daily life, such as content recommendation and security monitoring. To enhance video recognition development, many inst…
Consistent Estimation of Numerical Distributions under Local Differential Privacy by Wavelet Expansion
Puning Zhao, Zhikun Zhang, Bo Sun +4
Distribution estimation under local differential privacy (LDP) is a fundamental and challenging task. Significant progresses have been made on categorical data. However, due to dif…
Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning
Zhaoyang Chu, Yao Wan, Zhikun Zhang +7
While Code Language Models (CLMs) have demonstrated superior performance in software engineering tasks such as code generation and summarization, recent empirical studies reveal a…
GradEscape: A Gradient-Based Evader Against AI-Generated Text Detectors
Wenlong Meng, Shuguo Fan, Chengkun Wei +5
In this paper, we introduce GradEscape, the first gradient-based evader designed to attack AI-generated text (AIGT) detectors. GradEscape overcomes the undifferentiable computation…
Bilateral Differentially Private Vertical Federated Boosted Decision Trees
Bokang Zhang, Zhikun Zhang, Haodong Jiang +5
Federated learning is a distributed machine learning paradigm that enables collaborative training across multiple parties while ensuring data privacy. Gradient Boosting Decision Tr…
ArtistAuditor: Auditing Artist Style Pirate in Text-to-Image Generation Models
Linkang Du, Zheng Zhu, Min Chen +5
Text-to-image models based on diffusion processes, such as DALL-E, Stable Diffusion, and Midjourney, are capable of transforming texts into detailed images and have widespread appl…
CIBPU: A Conflict-Invisible Secure Branch Prediction Unit
Zhe Zhou, Fei Tong, Hongyu Wang +4
Previous schemes for designing secure branch prediction unit (SBPU) based on physical isolation can only offer limited security and significantly affect BPU's prediction capability…
PSGraph: Differentially Private Streaming Graph Synthesis by Considering Temporal Dynamics
Quan Yuan, Zhikun Zhang, Linkang Du +6
Streaming graphs are ubiquitous in daily life, such as evolving social networks and dynamic communication systems. Due to the sensitive information contained in the graph, directly…
SoK: Dataset Copyright Auditing in Machine Learning Systems
Linkang Du, Xuanru Zhou, Min Chen +5
As the implementation of machine learning (ML) systems becomes more widespread, especially with the introduction of larger ML models, we perceive a spring demand for massive data.…
NeRF: Privacy-preserving Training Framework for NeRF
Bokang Zhang, Yanglin Zhang, Zhikun Zhang +3
Neural Radiance Fields (NeRF) have revolutionized 3D computer vision and graphics, facilitating novel view synthesis and influencing sectors like extended reality and e-commerce. H…
Real-Time Trajectory Synthesis with Local Differential Privacy
Yujia Hu, Yuntao Du, Zhikun Zhang +4
Trajectory streams are being generated from location-aware devices, such as smartphones and in-vehicle navigation systems. Due to the sensitive nature of the location data, directl…
DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training
Zihao Wang, Rui Zhu, Dongruo Zhou +4
Recent developments have underscored the critical role of \textit{differential privacy} (DP) in safeguarding individual data for training machine learning models. However, integrat…
TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang +67
Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…
FAKEPCD: Fake Point Cloud Detection via Source Attribution
Yiting Qu, Zhikun Zhang, Yun Shen +2
To prevent the mischievous use of synthetic (fake) point clouds produced by generative models, we pioneer the study of detecting point cloud authenticity and attributing them to th…
The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
Xiaoyi Chen, Siyuan Tang, Rui Zhu +7
The rapid advancements of large language models (LLMs) have raised public concerns about the privacy leakage of personally identifiable information (PII) within their extensive tra…
InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model
Meng Tong, Kejiang Chen, Jie Zhang +5
Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks. However, they have also raised concerns about privacy risks such as data leakage and unau…
ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning
Linkang Du, Min Chen, Mingyang Sun +4
Data is a critical asset in AI, as high-quality datasets can significantly improve the performance of machine learning models. In safety-critical domains such as autonomous vehicle…
LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors
Chengkun Wei, Wenlong Meng, Zhikun Zhang +6
Prompt-tuning has emerged as an attractive paradigm for deploying large-scale language models due to its strong downstream task performance and efficient multitask serving ability.…
Generated Graph Detection
Yihan Ma, Zhikun Zhang, Ning Yu +4
Graph generative models become increasingly effective for data distribution approximation and data augmentation. While they have aroused public concerns about their malicious misus…
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning
Chengkun Wei, Minghu Zhao, Zhikun Zhang +5
Differential privacy (DP), as a rigorous mathematical definition quantifying privacy leakage, has become a well-accepted standard for privacy protection. Combined with powerful mac…