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Automatic Rule Extraction from Access Rules Using Genetic Programming

机译:使用遗传编程从访问规则中自动提取规则

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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 CP-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:公司中的安全策略规则通常由首席安全官(CSO)提出,他必须例如手动选择允许哪些访问事件和应该禁止哪些访问事件。在这项工作中,我们提出了一种使用遗传编程(GP)自动获取将这些基于单事件的规则进行概括的规则的方法,此外,该方法还应该能够以一种易于理解的方式来呈现它们。在以编码个体的方式测试了不同的适应度函数和配置之后,我们基于CP的系统获得了良好的数据集覆盖率,并且在模拟结果中相对于真实数据的假阳性和假阴性比率很小。

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