1 code implementation • 23 Nov 2022 • Soodeh Atefi, Sakshyam Panda, Emmanouil Panaousis, Aron Laszka
A recent study demonstrated that data-driven decision support, based on a dataset of prior incidents, can provide state-of-the-art prioritization.
no code implementations • 24 Jun 2022 • Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang
Federated learning is an emerging concept in the domain of distributed machine learning.
no code implementations • 24 Jun 2022 • Yuhang Tian, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang
In this work, we propose FLVoogd, an updated federated learning method in which servers and clients collaboratively eliminate Byzantine attacks while preserving privacy.
no code implementations • 3 Nov 2021 • Sakshyam Panda, Stefan Rass, Sotiris Moschoyiannis, Kaitai Liang, George Loukas, Emmanouil Panaousis
By taking a game-theoretic approach, we model the adversarial interaction as a repeated imperfect-information zero-sum game in which the IoV network administrator chooses a set of vulnerabilities to offer in a honeypot and a strategic attacker chooses a vulnerability of the IoV to exploit under uncertainty.