What Is Your MOVE

Modeling Adversarial Network Environments

Conference paper (2020)

Authors

Karlo Knezevic University of Zagreb
S. Picek Cyber Security - EEMCS
Domagoj Jakobovic University of Zagreb
JC Hernandez-Castro University of Kent
Research Group
Cyber Security (EEMCS) (TU Delft)
Copyright: © 2020 Karlo Knezevic, S. Picek, Domagoj Jakobovic, Julio Hernandez-Castro
DOI
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https://doi.org/10.1007/978-3-030-43722-0_17
Network security Attack/defense strategies Coevolutionary algorithms
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Published Date

2020

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Cyber Security

Abstract

Finding optimal adversarial dynamics between defenders and attackers in large network systems is a complex problem one can approach from several perspectives. The results obtained are often not satisfactory since they either concentrate on only one party or run very simplified scenarios that are hard to correlate with realistic settings. To truly find which are the most robust defensive strategies, the adaptive attacker ecosystem must be given as many degrees of freedom as possible, to model real attacking scenarios accurately. We propose a coevolutionary-based simulator called MOVE that can evolve both attack and defense strategies. To test it, we investigate several different but realistic scenarios, taking into account features such as network topology and possible applications in the network. The results show that the evolved strategies far surpass randomly generated strategies. Finally, the evolved strategies can help us to reach some more general conclusions for both attacker and defender sides.