Work

Attackers Can Do Better: Over- and Understated Factors of Model Stealing Attacks

Year: 2025

Type: conference-paper

Source: IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)

DOI: 10.1109/satml64287.2025.00016

Authors: Daryna Oliynyk, Rudolf Mayer, Andreas Rauber

Institutions: University of Vienna, SBA Research, TU Wien

Language: English

Topic: Adversarial Robustness in Machine Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4410609024

FWCI: 0.984

Cites: 54

Cited by: 1

Related to: 10