LUDUS - Collaborative defense against internet attacks by standing learning and game theory

The aim of the Ludus project is to increase the safety of a large group of Internet users through machine learning and game theory with collaborative defense applied to network traffic. Developed software will be automated to defend based on shared and centralized network user metadata, analysis of attack behaviors, and a collaborative defense strategy.

Partial goals are as follows:

1. Measure your current network security
2. Detect attacks using behavioral patterns
3. Create gaming models and defense strategies that will account for the behavior of all attackers at the same time.
4. Implement automated software to implement network strategies.