most citedOn the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused?

5 citations · 16 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2024

Data Free Backdoor Attacks

Bochuan Cao, Jinyuan Jia, Chuxuan Hu +5

Backdoor attacks aim to inject a backdoor into a classifier such that it predicts any input with an attacker-chosen backdoor trigger as an attacker-chosen target class. Existing ba…

cs.CR2024

ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning

Zhangchen Xu, Fengqing Jiang, Luyao Niu +3

In Federated Learning (FL), a set of clients collaboratively train a machine learning model (called global model) without sharing their local training data. The local training data…

cs.CR2024★ 3 cited

SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding

Zhangchen Xu, Fengqing Jiang, Luyao Niu +3

As large language models (LLMs) become increasingly integrated into real-world applications such as code generation and chatbot assistance, extensive efforts have been made to alig…

cs.LG2024

Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning

Zhangchen Xu, Fengqing Jiang, Luyao Niu +2

Federated learning (FL) enables multiple participants to train a global machine learning model without sharing their private training data. Peer-to-peer (P2P) FL advances existing…

cs.CR2023★ 4 cited

Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications

Fengqing Jiang, Zhangchen Xu, Luyao Niu +4

Large language models (LLMs) are increasingly deployed as the service backend for LLM-integrated applications such as code completion and AI-powered search. LLM-integrated applicat…

cs.LG2023★ 1 cited

TextGuard: Provable Defense against Backdoor Attacks on Text Classification

Hengzhi Pei, Jinyuan Jia, Wenbo Guo +2

Backdoor attacks have become a major security threat for deploying machine learning models in security-critical applications. Existing research endeavors have proposed many defense…

cs.CV2023★ 3 cited

IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI

Bochuan Cao, Changjiang Li, Ting Wang +3

Diffusion-based image generation models, such as Stable Diffusion or DALL-E 2, are able to learn from given images and generate high-quality samples following the guidance from pro…

cs.LG2023★ 5 cited

On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused?

Hangfan Zhang, Zhimeng Guo, Huaisheng Zhu +5

Large Language Models (LLMs) have achieved unprecedented performance in Natural Language Generation (NLG) tasks. However, many existing studies have shown that they could be misuse…