37 citations · 51 across the 6 of their papers we have counts for
7 papers
SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version)
Phillip Rieger, Alessandro Pegoraro, Kavita Kumari +3
Split Learning (SL) is a distributed deep learning approach enabling multiple clients and a server to collaboratively train and infer on a shared deep neural network (DNN) without…
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
Kavita Kumari, Murtuza Jadliwala, Sumit Kumar Jha +1
Model explanations improve the transparency of black-box machine learning (ML) models and their decisions; however, they can also be exploited to carry out privacy threats such as…
DeepEclipse: How to Break White-Box DNN-Watermarking Schemes
Alessandro Pegoraro, Carlotta Segna, Kavita Kumari +1
Deep Learning (DL) models have become crucial in digital transformation, thus raising concerns about their intellectual property rights. Different watermarking techniques have been…
DEMASQ: Unmasking the ChatGPT Wordsmith
Kavita Kumari, Alessandro Pegoraro, Hossein Fereidooni +1
The potential misuse of ChatGPT and other Large Language Models (LLMs) has raised concerns regarding the dissemination of false information, plagiarism, academic dishonesty, and fr…
To ChatGPT, or not to ChatGPT: That is the question!
Alessandro Pegoraro, Kavita Kumari, Hossein Fereidooni +1
ChatGPT has become a global sensation. As ChatGPT and other Large Language Models (LLMs) emerge, concerns of misusing them in various ways increase, such as disseminating fake news…
BayBFed: Bayesian Backdoor Defense for Federated Learning
Kavita Kumari, Phillip Rieger, Hossein Fereidooni +2
Federated learning (FL) allows participants to jointly train a machine learning model without sharing their private data with others. However, FL is vulnerable to poisoning attacks…