4 citations · 5 across the 4 of their papers we have counts for
4 papers
Bypassing LLM Guardrails: An Empirical Analysis of Evasion Attacks against Prompt Injection and Jailbreak Detection Systems
William Hackett, Lewis Birch, Stefan Trawicki +2
Large Language Models (LLMs) guardrail systems are designed to protect against prompt injection and jailbreak attacks. However, they remain vulnerable to evasion techniques. We dem…
Compilation as a Defense: Enhancing DL Model Attack Robustness via Tensor Optimization
Stefan Trawicki, William Hackett, Lewis Birch +2
Adversarial Machine Learning (AML) is a rapidly growing field of security research, with an often overlooked area being model attacks through side-channels. Previous works show suc…
Model Leeching: An Extraction Attack Targeting LLMs
Lewis Birch, William Hackett, Stefan Trawicki +2
Model Leeching is a novel extraction attack targeting Large Language Models (LLMs), capable of distilling task-specific knowledge from a target LLM into a reduced parameter model.…
PINCH: An Adversarial Extraction Attack Framework for Deep Learning Models
William Hackett, Stefan Trawicki, Zhengxin Yu +2
Adversarial extraction attacks constitute an insidious threat against Deep Learning (DL) models in-which an adversary aims to steal the architecture, parameters, and hyper-paramete…