37 citations · 73 across the 5 of their papers we have counts for
9 papers
Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning (Full Version)
Jonathan Knauer, Phillip Rieger, Hossein Fereidooni +1
Deep Neural Networks (DNNs) can handle increasingly complex tasks, albeit they require rapidly expanding training datasets. Collecting data from platforms with user-generated conte…
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning
Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger +2
Federated learning (FL) is a collaborative learning paradigm allowing multiple clients to jointly train a model without sharing their training data. However, FL is susceptible to p…
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…
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks
Jorge Castillo, Phillip Rieger, Hossein Fereidooni +2
Federated learning (FL) is a distributed learning process that uses a trusted aggregation server to allow multiple parties (or clients) to collaboratively train a machine learning…
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…
ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning
Oliver Lutz, Huili Chen, Hossein Fereidooni +4
Ethereum smart contracts are automated decentralized applications on the blockchain that describe the terms of the agreement between buyers and sellers, reducing the need for trust…