Abstract
We apply Grammatical Evolution (GE), and multi population competitive coevolutionary algorithms to the domain of cybersecurity. Our interest (and concern) is the evolution of network denial of service attacks. In these cases, when attackers are deterred by a specific defense, they evolve their strategies until variations find success. Defenders are then forced to counter the new variations and an arms race ensues. We use GE and grammars to conveniently express and explore the behavior of network defenses and denial of service attacks under different mission and network scenarios. We use coevolution to model competition between attacks and defenses and the larger scale arms race. This allows us to study the dynamics and the solutions of the competing adversaries.
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Notes
- 1.
In RIVALS’ implementation, Python’s random library is used.
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This material is based upon the work supported by DARPA. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements. Either expressed or implied of Applied Communication Services, or the US Government.
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Hemberg, E., Lugo, A.E., Garcia, D., O’Reilly, UM. (2018). Grammatical Evolution with Coevolutionary Algorithms in Cyber Security. In: Ryan, C., O'Neill, M., Collins, J. (eds) Handbook of Grammatical Evolution. Springer, Cham. https://doi.org/10.1007/978-3-319-78717-6_17
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DOI: https://doi.org/10.1007/978-3-319-78717-6_17
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