16 citations · 50 across the 15 of their papers we have counts for
16 papers
LongPIBench: A Long-Context Benchmark for Prompt Injection
Yupei Liu, Yuqi Jia, Neil Zhenqiang Gong +1
Prompt injection attacks pose a serious security risk to large language models in real-world applications. However, existing prompt injection benchmarks primarily focus on short-co…
PromptLocate: Localizing Prompt Injection Attacks
Yuqi Jia, Yupei Liu, Zedian Shao +2
Prompt injection attacks deceive a large language model into completing an attacker-specified task instead of its intended task by contaminating its input data with an injected pro…
PIShield: Detecting Prompt Injection Attacks via Intrinsic LLM Features
Wei Zou, Yupei Liu, Yanting Wang +3
LLM-integrated applications are vulnerable to prompt injection attacks, where an attacker contaminates the input to inject malicious instructions, causing the LLM to follow the att…
SecInfer: Preventing Prompt Injection via Inference-time Scaling
Yupei Liu, Yanting Wang, Yuqi Jia +2
Prompt injection attacks pose a pervasive threat to the security of Large Language Models (LLMs). State-of-the-art prevention-based defenses typically rely on fine-tuning an LLM to…
A Critical Evaluation of Defenses against Prompt Injection Attacks
Yuqi Jia, Zedian Shao, Yupei Liu +3
Large Language Models (LLMs) are vulnerable to prompt injection attacks, and several defenses have recently been proposed, often claiming to mitigate these attacks successfully. Ho…
DataSentinel: A Game-Theoretic Detection of Prompt Injection Attacks
Yupei Liu, Yuqi Jia, Jinyuan Jia +2
LLM-integrated applications and agents are vulnerable to prompt injection attacks, where an attacker injects prompts into their inputs to induce attacker-desired outputs. A detecti…
SecureGaze: Defending Gaze Estimation Against Backdoor Attacks
Lingyu Du, Yupei Liu, Jinyuan Jia +1
Gaze estimation models are widely used in applications such as driver attention monitoring and human-computer interaction. While many methods for gaze estimation exist, they rely h…
TrojanDec: Data-free Detection of Trojan Inputs in Self-supervised Learning
Yupei Liu, Yanting Wang, Jinyuan Jia
An image encoder pre-trained by self-supervised learning can be used as a general-purpose feature extractor to build downstream classifiers for various downstream tasks. However, m…
Defending Deep Regression Models against Backdoor Attacks
Lingyu Du, Yupei Liu, Jinyuan Jia +1
Deep regression models are used in a wide variety of safety-critical applications, but are vulnerable to backdoor attacks. Although many defenses have been proposed for classificat…
Evaluating LLM-based Personal Information Extraction and Countermeasures
Yupei Liu, Yuqi Jia, Jinyuan Jia +1
Automatically extracting personal information -- such as name, phone number, and email address -- from publicly available profiles at a large scale is a stepstone to many other sec…
Formalizing and Benchmarking Prompt Injection Attacks and Defenses
Yupei Liu, Yuqi Jia, Runpeng Geng +2
A prompt injection attack aims to inject malicious instruction/data into the input of an LLM-Integrated Application such that it produces results as an attacker desires. Existing w…
PORE: Provably Robust Recommender Systems against Data Poisoning Attacks
Jinyuan Jia, Yupei Liu, Yuepeng Hu +1
Data poisoning attacks spoof a recommender system to make arbitrary, attacker-desired recommendations via injecting fake users with carefully crafted rating scores into the recomme…
StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning
Yupei Liu, Jinyuan Jia, Hongbin Liu +1
Pre-trained encoders are general-purpose feature extractors that can be used for many downstream tasks. Recent progress in self-supervised learning can pre-train highly effective e…
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning
Jinyuan Jia, Yupei Liu, Neil Zhenqiang Gong
Self-supervised learning in computer vision aims to pre-train an image encoder using a large amount of unlabeled images or (image, text) pairs. The pre-trained image encoder can th…
Security Analysis of Camera-LiDAR Fusion Against Black-Box Attacks on Autonomous Vehicles
R. Spencer Hallyburton, Yupei Liu, Yulong Cao +2
To enable safe and reliable decision-making, autonomous vehicles (AVs) feed sensor data to perception algorithms to understand the environment. Sensor fusion with multi-frame track…
Certified Robustness of Nearest Neighbors against Data Poisoning and Backdoor Attacks
Jinyuan Jia, Yupei Liu, Xiaoyu Cao +1
Data poisoning attacks and backdoor attacks aim to corrupt a machine learning classifier via modifying, adding, and/or removing some carefully selected training examples, such that…