Search Results for author:
Found 6 papers, 1 papers with code
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
By means of a comprehensive set of simulations of the proposed game model, we assess different factors that can impact the capability of an adversary to launch MIA in such repeated interaction settings.
DeepEclipse: How to Break White-Box DNN-Watermarking Schemes
Deep Learning (DL) models have become crucial in digital transformation, thus raising concerns about their intellectual property rights.
DEMASQ: Unmasking the ChatGPT Wordsmith
The potential misuse of ChatGPT and other Large Language Models (LLMs) has raised concerns regarding the dissemination of false information, plagiarism, academic dishonesty, and fraudulent activities.
To ChatGPT, or not to ChatGPT: That is the question!
The dataset serves as a reference to assess the performance of various techniques in detecting ChatGPT-generated content.
BayBFed: Bayesian Backdoor Defense for Federated Learning
However, as these approaches directly operate on client updates, their effectiveness depends on factors such as clients' data distribution or the adversary's attack strategies.
A Game-theoretic Understanding of Repeated Explanations in ML Models
This paper formally models the strategic repeated interactions between a system, comprising of a machine learning (ML) model and associated explanation method, and an end-user who is seeking a prediction/label and its explanation for a query/input, by means of game theory.
