129 citations · 312 across the 40 of their papers we have counts for
4 papers · 1 filter
Label Inference Attacks against Node-level Vertical Federated GNNs
Marco Arazzi, Mauro Conti, Stefanos Koffas +4
Federated learning enables collaborative training of machine learning models by keeping the raw data of the involved workers private. Three of its main objectives are to improve th…
Turning Privacy-preserving Mechanisms against Federated Learning
Marco Arazzi, Mauro Conti, Antonino Nocera +1
Recently, researchers have successfully employed Graph Neural Networks (GNNs) to build enhanced recommender systems due to their capability to learn patterns from the interaction b…
An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework
Ehsan Nowroozi, Abhishek, Mohammadreza Mohammadi +1
Malicious advertisement URLs pose a security risk since they are the source of cyber-attacks, and the need to address this issue is growing in both industry and academia. Generally…
On Defending Against Label Flipping Attacks on Malware Detection Systems
Rahim Taheri, Reza Javidan, Mohammad Shojafar +3
Label manipulation attacks are a subclass of data poisoning attacks in adversarial machine learning used against different applications, such as malware detection. These types of a…