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Automatic Rule Extraction from Access Rules Using Genetic Programming

机译:使用基因编程自动提取访问规则

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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 generalise 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.
机译:公司的安全政策规则通常由首席安全官(CSO)提出,该规则必须通过允许访问事件以及应禁止允许访问事件的手来选择。 在这项工作中,我们提出了一种方法来自动获得使用基因编程(GP)概括基于单一事件的规则的规则,除此之外,这应该能够以可理解的方式呈现它们。 我们基于GP的系统获得了良好的数据集覆盖范围和模拟中的误报和否定的小比例在对个人的方式测试不同的健身功能和配置之后,在实际数据之后,在实际数据之后。

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