no code implementations • 20 Sep 2023 • Stefan Trawicki, William Hackett, Lewis Birch, Neeraj Suri, Peter Garraghan
Adversarial Machine Learning (AML) is a rapidly growing field of security research, with an often overlooked area being model attacks through side-channels.
no code implementations • 19 Sep 2023 • Lewis Birch, William Hackett, Stefan Trawicki, Neeraj Suri, Peter Garraghan
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.
no code implementations • 13 Sep 2022 • William Hackett, Stefan Trawicki, Zhengxin Yu, Neeraj Suri, Peter Garraghan
Adversarial extraction attacks constitute an insidious threat against Deep Learning (DL) models in-which an adversary aims to steal the architecture, parameters, and hyper-parameters of a targeted DL model.
1 code implementation • 11 Oct 2021 • Shreshth Tuli, Sukhpal Singh Gill, Minxian Xu, Peter Garraghan, Rami Bahsoon, Schahram Dustdar, Rizos Sakellariou, Omer Rana, Rajkumar Buyya, Giuliano Casale, Nicholas R. Jennings
The worldwide adoption of cloud data centers (CDCs) has given rise to the ubiquitous demand for hosting application services on the cloud.