The main premise of federated learning (FL) is that machine learning model updates are
computed locally to preserve user data privacy. This approach avoids by design user data to …

Deep neural networks have been shown vulnerable to adversarial examples. Even though
many defense methods have been proposed to enhance the robustness, it is still a long way …

Deep neural networks are vulnerable to adversarial attacks. In this paper, we take the role of
investigators who want to trace the attack and identify the source, that is, the particular model …

In this paper, we tackle the issue of moral hazard within the realm of the vehicular
Metaverse. A pivotal facilitator of the vehicular Metaverse is the effective orchestration of its …

The vehicular Metaverse represents an emerging paradigm that merges vehicular
communications with virtual environments, integrating real-world data to enhance in-vehicle …

In this paper, we tackle the issue of moral hazard within the realm of the vehicular
Metaverse. A pivotal facilitator of the vehicular Metaverse is the effective orchestration of its …

In the seller-buyer setting on machine learning models, the seller generates different copies
based on the original model and distributes them to different buyers, such that adversarial …

Adversarial attacks are types of attacks where adversaries try to deceive the machine
learning algorithm by providing deceptive input. Adversarial attacks are focused on …