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Found 4 papers, 1 papers with code
Principled Data-Driven Decision Support for Cyber-Forensic Investigations
A recent study demonstrated that data-driven decision support, based on a dataset of prior incidents, can provide state-of-the-art prioritization.
MULTI-FLGANs: Multi-Distributed Adversarial Networks for Non-IID distribution
Federated learning is an emerging concept in the domain of distributed machine learning.
FLVoogd: Robust And Privacy Preserving Federated Learning
In this work, we propose FLVoogd, an updated federated learning method in which servers and clients collaboratively eliminate Byzantine attacks while preserving privacy.
HoneyCar: A Framework to Configure HoneypotVulnerabilities on the Internet of Vehicles
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.
