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20212026
most citedPrivacy for Free: How does Dataset Condensation Help Privacy?

31 citations · 48 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CR2026

Evaluating and Improving Static Application Security Testing Tools for Rust

Huaien Zhang, Zhengjie Zhao, Yu Pei +4

Rust has become a popular systems programming language in recent years because of its strong guarantees on memory and concurrency safety. Many types of system software have been re…

cs.CR2026

Chaining Skills to Hijack LLM Agents

Tian Dong, Zixuan Ma, Haodong Zhao +3

LLM agents use skills to improve performance on specialized tasks. To complete a user request, an agent may invoke several skills in sequence, allowing information produced under o…

cs.SE2026

VulnGym: Benchmarking Coding Agents for Repository-Level Vulnerability Detection

Kexing Ji, Jiachen Liu, Enze Hu +7

Recent advances in LLM-based vulnerability detection have shown promising results, while coding agents further extend this capability from isolated code snippets to complete reposi…

cs.AI2026

Measuring Behavior Portability in Large Language Models

Tianjia Dong, Nadav Kunievsky, James A. Evans

Large language models are increasingly deployed as autonomous decision makers, yet the behavioral mapping they exhibit can vary substantially across decision environments that are…

cs.CR2026

DIPBox: A Multi-scale Testing Framework for Tracking Dataset Regeneration

Tian Dong, Yan Meng, Shaofeng Li +5

Training datasets have tremendous proprietary value and are vulnerable to unauthorized copying. Existing defenses mainly focus on tracking individual data points, but pay little at…

cs.CR2026

AgentRAE: Remote Action Execution through Notification-based Visual Backdoors against Screenshots-based Mobile GUI Agents

Yutao Luo, Haotian Zhu, Shuchao Pang +4

The rapid adoption of mobile graphical user interface (GUI) agents, which autonomously control applications and operating systems (OS), exposes new system-level attack surfaces. Ex…

cs.CR2025

Authority Backdoor: A Certifiable Backdoor Mechanism for Authoring DNNs

Han Yang, Shaofeng Li, Tian Dong +3

Deep Neural Networks (DNNs), as valuable intellectual property, face unauthorized use. Existing protections, such as digital watermarking, are largely passive; they provide only po…

cs.CR2022

Mind Your Heart: Stealthy Backdoor Attack on Dynamic Deep Neural Network in Edge Computing

Tian Dong, Ziyuan Zhang, Han Qiu +3

Transforming off-the-shelf deep neural network (DNN) models into dynamic multi-exit architectures can achieve inference and transmission efficiency by fragmenting and distributing…

cs.CR2022★ 31 cited

Privacy for Free: How does Dataset Condensation Help Privacy?

Tian Dong, Bo Zhao, Lingjuan Lyu

To prevent unintentional data leakage, research community has resorted to data generators that can produce differentially private data for model training. However, for the sake of…

cs.CR2022★ 7 cited

An Interpretable Federated Learning-based Network Intrusion Detection Framework

Tian Dong, Song Li, Han Qiu +1

Learning-based Network Intrusion Detection Systems (NIDSs) are widely deployed for defending various cyberattacks. Existing learning-based NIDS mainly uses Neural Network (NN) as a…

cs.CR2021★ 1 cited

Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors

Ruoxi Sun, Minhui Xue, Gareth Tyson +6

Numerous open-source and commercial malware detectors are available. However, their efficacy is threatened by new adversarial attacks, whereby malware attempts to evade detection,…

cs.CR2021★ 4 cited

Fingerprinting Multi-exit Deep Neural Network Models via Inference Time

Tian Dong, Han Qiu, Tianwei Zhang +3

Transforming large deep neural network (DNN) models into the multi-exit architectures can overcome the overthinking issue and distribute a large DNN model on resource-constrained s…

cs.CL2021★ 5 cited

Hidden Backdoors in Human-Centric Language Models

Shaofeng Li, Hui Liu, Tian Dong +4

Natural language processing (NLP) systems have been proven to be vulnerable to backdoor attacks, whereby hidden features (backdoors) are trained into a language model and may only…