Cerberus: Exploring Federated Prediction of Security Events. (arXiv:2209.03050v1 [cs.CR])

Modern defenses against cyberattacks increasingly rely on proactive
approaches, e.g., to predict the adversary's next actions based on past events.
Building accurate prediction models requires knowledge from many organizations;
alas, this entails disclosing sensitive information, such as network
structures, security postures, and policies, which might often be undesirable
or outright impossible. In this paper, we explore the feasibility of using
Federated Learning (FL) to predict future security events. To this end, we
introduce Cerberus, a system enabling collaborative training of …

events prediction security