111 citations · 361 across the 12 of their papers we have counts for
12 papers
PentestGPT: An LLM-empowered Automatic Penetration Testing Tool
Gelei Deng, Yi Liu, Víctor Mayoral-Vilches +7
Penetration testing, a crucial industrial practice for ensuring system security, has traditionally resisted automation due to the extensive expertise required by human professional…
MasterKey: Automated Jailbreak Across Multiple Large Language Model Chatbots
Gelei Deng, Yi Liu, Yuekang Li +6
Large Language Models (LLMs) have revolutionized Artificial Intelligence (AI) services due to their exceptional proficiency in understanding and generating human-like text. LLM cha…
Multi-target Backdoor Attacks for Code Pre-trained Models
Yanzhou Li, Shangqing Liu, Kangjie Chen +3
Backdoor attacks for neural code models have gained considerable attention due to the advancement of code intelligence. However, most existing works insert triggers into task-speci…
Prompt Injection attack against LLM-integrated Applications
Yi Liu, Gelei Deng, Yuekang Li +9
Large Language Models (LLMs), renowned for their superior proficiency in language comprehension and generation, stimulate a vibrant ecosystem of applications around them. However,…
Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study
Yi Liu, Gelei Deng, Zhengzi Xu +7
Large Language Models (LLMs), like ChatGPT, have demonstrated vast potential but also introduce challenges related to content constraints and potential misuse. Our study investigat…
SoK: Rethinking Sensor Spoofing Attacks against Robotic Vehicles from a Systematic View
Yuan Xu, Xingshuo Han, Gelei Deng +3
Robotic Vehicles (RVs) have gained great popularity over the past few years. Meanwhile, they are also demonstrated to be vulnerable to sensor spoofing attacks. Although a wealth of…
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Shangwei Guo, Xu Zhang, Fei Yang +4
With the rapid demand of data and computational resources in deep learning systems, a growing number of algorithms to utilize collaborative machine learning techniques, for example…
Privacy-preserving Collaborative Learning with Automatic Transformation Search
Wei Gao, Shangwei Guo, Tianwei Zhang +3
Collaborative learning has gained great popularity due to its benefit of data privacy protection: participants can jointly train a Deep Learning model without sharing their trainin…
Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models
Shangwei Guo, Tianwei Zhang, Han Qiu +3
Watermarking has become the tendency in protecting the intellectual property of DNN models. Recent works, from the adversary's perspective, attempted to subvert watermarking mechan…
Topology-aware Differential Privacy for Decentralized Image Classification
Shangwei Guo, Tianwei Zhang, Guowen Xu +3
In this paper, we design Top-DP, a novel solution to optimize the differential privacy protection of decentralized image classification systems. The key insight of our solution is…
Stealing Deep Reinforcement Learning Models for Fun and Profit
Kangjie Chen, Shangwei Guo, Tianwei Zhang +2
This paper presents the first model extraction attack against Deep Reinforcement Learning (DRL), which enables an external adversary to precisely recover a black-box DRL model only…
Byzantine-resilient Decentralized Stochastic Gradient Descent
Shangwei Guo, Tianwei Zhang, Han Yu +4
Decentralized learning has gained great popularity to improve learning efficiency and preserve data privacy. Each computing node makes equal contribution to collaboratively learn a…