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Automatic rule extraction from access rules using Genetic Programming

Abstract : The security policy rules in companies are generally proposed by the Chief Security Officer (CSO), who must, for instance, select by hand which access events are allowed and which ones should be forbidden. In this work we propose a way to automatically obtain rules that gen-eralise these single-event based rules using Genetic Programming (GP), which, besides, should be able to present them in an understandable way. Our GP-based system obtains good dataset coverage and small ratios of false positives and negatives in the simulation results over real data, after testing different fitness functions and configurations in the way of coding the individuals.
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Submitted on : Thursday, June 25, 2020 - 5:21:20 PM
Last modification on : Saturday, June 25, 2022 - 7:42:43 PM
Long-term archiving on: : Wednesday, September 23, 2020 - 4:06:41 PM


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  • HAL Id : hal-02880764, version 1


Paloma de Las Cuevas, Pablo Garcia-Sanchez, Zaineb Chelly Dagdia, Maria-Isabel Garcia-Arenas, Juan Julian Merelo. Automatic rule extraction from access rules using Genetic Programming. EvoCOP 2020 - 20th European Conference on Evolutionary Computation in Combinatorial Optimisation, Apr 2020, Seville, Spain. ⟨hal-02880764⟩



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