111 citations · 517 across the 26 of their papers we have counts for
27 papers
IllusionCAPTCHA: A CAPTCHA based on Visual Illusion
Ziqi Ding, Gelei Deng, Yi Liu +4
CAPTCHAs have long been essential tools for protecting applications from automated bots. Initially designed as simple questions to distinguish humans from bots, they have become in…
Detecting LLM Fact-conflicting Hallucinations Enhanced by Temporal-logic-based Reasoning
Ningke Li, Yahui Song, Kailong Wang +4
Large language models (LLMs) face the challenge of hallucinations -- outputs that seem coherent but are actually incorrect. A particularly damaging type is fact-conflicting halluci…
TombRaider: Entering the Vault of History to Jailbreak Large Language Models
Junchen Ding, Jiahao Zhang, Yi Liu +3
Warning: This paper contains content that may involve potentially harmful behaviours, discussed strictly for research purposes. Jailbreak attacks can hinder the safety of Large Lan…
Image-Based Geolocation Using Large Vision-Language Models
Yi Liu, Junchen Ding, Gelei Deng +6
Geolocation is now a vital aspect of modern life, offering numerous benefits but also presenting serious privacy concerns. The advent of large vision-language models (LVLMs) with a…
Continuous Embedding Attacks via Clipped Inputs in Jailbreaking Large Language Models
Zihao Xu, Yi Liu, Gelei Deng +4
Security concerns for large language models (LLMs) have recently escalated, focusing on thwarting jailbreaking attempts in discrete prompts. However, the exploration of jailbreak v…
Source Code Summarization in the Era of Large Language Models
Weisong Sun, Yun Miao, Yuekang Li +6
To support software developers in understanding and maintaining programs, various automatic (source) code summarization techniques have been proposed to generate a concise natural…
Uncovering Logit Suppression Vulnerabilities in LLM Safety Alignment
Yuxi Li, Yi Liu, Yuekang Li +4
Large language models (LLMs) have revolutionized various applications, making robust safety alignment essential to prevent harmful outputs. Current safety alignment techniques, how…
Drowzee: Metamorphic Testing for Fact-Conflicting Hallucination Detection in Large Language Models
Ningke Li, Yuekang Li, Yi Liu +3
Large language models (LLMs) have transformed the landscape of language processing, yet struggle with significant challenges in terms of security, privacy, and the generation of se…
Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection
Yuxi Li, Yi Liu, Gelei Deng +7
With the expanding application of Large Language Models (LLMs) in various domains, it becomes imperative to comprehensively investigate their unforeseen behaviors and consequent ou…
MeTMaP: Metamorphic Testing for Detecting False Vector Matching Problems in LLM Augmented Generation
Guanyu Wang, Yuekang Li, Yi Liu +6
Augmented generation techniques such as Retrieval-Augmented Generation (RAG) and Cache-Augmented Generation (CAG) have revolutionized the field by enhancing large language model (L…
Pandora: Jailbreak GPTs by Retrieval Augmented Generation Poisoning
Gelei Deng, Yi Liu, Kailong Wang +3
Large Language Models~(LLMs) have gained immense popularity and are being increasingly applied in various domains. Consequently, ensuring the security of these models is of paramou…
A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models
Zihao Xu, Yi Liu, Gelei Deng +2
Large Language Models (LLMS) have increasingly become central to generating content with potential societal impacts. Notably, these models have demonstrated capabilities for genera…
MiniScope: Automated UI Exploration and Privacy Inconsistency Detection of MiniApps via Two-phase Iterative Hybrid Analysis
Shenao Wang, Yuekang Li, Kailong Wang +4
The advent of MiniApps, operating within larger SuperApps, has revolutionized user experiences by offering a wide range of services without the need for individual app downloads. H…
A Survey of Protocol Fuzzing
Xiaohan Zhang, Cen Zhang, Xinghua Li +8
Communication protocols form the bedrock of our interconnected world, yet vulnerabilities within their implementations pose significant security threats. Recent developments have s…
Digger: Detecting Copyright Content Mis-usage in Large Language Model Training
Haodong Li, Gelei Deng, Yi Liu +7
Pre-training, which utilizes extensive and varied datasets, is a critical factor in the success of Large Language Models (LLMs) across numerous applications. However, the detailed…
ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers
Yi Liu, Yuekang Li, Gelei Deng +7
The popularity of automatic speech recognition (ASR) systems nowadays leads to an increasing need for improving their accessibility. Handling stuttering speech is an important feat…
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…
How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation
Cen Zhang, Yaowen Zheng, Mingqiang Bai +6
LLM-based (Large Language Model) fuzz driver generation is a promising research area. Unlike traditional program analysis-based method, this text-based approach is more general and…
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…
ACETest: Automated Constraint Extraction for Testing Deep Learning Operators
Jingyi Shi, Yang Xiao, Yuekang Li +6
Deep learning (DL) applications are prevalent nowadays as they can help with multiple tasks. DL libraries are essential for building DL applications. Furthermore, DL operators are…
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,…
Automatic Code Summarization via ChatGPT: How Far Are We?
Weisong Sun, Chunrong Fang, Yudu You +10
To support software developers in understanding and maintaining programs, various automatic code summarization techniques have been proposed to generate a concise natural language…
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…
Morest: Model-based RESTful API Testing with Execution Feedback
Yi Liu, Yuekang Li, Gelei Deng +6
RESTful APIs are arguably the most popular endpoints for accessing Web services. Blackbox testing is one of the emerging techniques for ensuring the reliability of RESTful APIs. Th…