220 citations · 277 across the 5 of their papers we have counts for
7 papers
ANT: A Multi-Granularity Network Traffic Dataset and Benchmark for Agents Behavior Auditing
Fan Li, Xiangyu Gao, Zixuan Liu +4
The growing adoption of large language model (LLM) agents creates a need for network administrators and security teams to audit agent behavior within organizational networks withou…
When Words Are Safe But Actions Kill: Probing Physical Jailbreak Beyond Textual Jailbreak in Hidden-State Risk Space
Weimeng Wang, Ziqiang Wang, Zihang Zhan +3
Large language models (LLMs) increasingly serve as high-level planners for embodied agents, where linguistically benign instructions can become unsafe once grounded in the physical…
A Hard-Label Black-Box Evasion Attack against ML-based Malicious Traffic Detection Systems
Zixuan Liu, Yi Zhao, Zhuotao Liu +4
Machine Learning (ML)-based malicious traffic detection is a promising security paradigm. It outperforms rule-based traditional detection by identifying various advanced attacks. H…
Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems
Tianyu Cui, Yanling Wang, Chuanpu Fu +13
Large language models (LLMs) have strong capabilities in solving diverse natural language processing tasks. However, the safety and security issues of LLM systems have become the m…
Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis
Chuanpu Fu, Qi Li, Ke Xu
In this paper, we propose HyperVision, a realtime unsupervised machine learning (ML) based malicious traffic detection system. Particularly, HyperVision is able to detect unknown p…
Realtime Robust Malicious Traffic Detection via Frequency Domain Analysis
Chuanpu Fu, Qi Li, Meng Shen +1
Machine learning (ML) based malicious traffic detection is an emerging security paradigm, particularly for zero-day attack detection, which is complementary to existing rule based…
Off-Path TCP Exploits of the Mixed IPID Assignment
Xuewei Feng, Chuanpu Fu, Qi Li +2
In this paper, we uncover a new off-path TCP hijacking attack that can be used to terminate victim TCP connections or inject forged data into victim TCP connections by manipulating…