Vulnerability Identification on GNU/Linux Operating Systems through Case-Based Reasoning

D. Santos, J. Nobre
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Abstract

Operating system security has been steadily evolving over the years. Several mechanisms, softwares and guides of best practices of configuration have been developed to contribute with the security of such systems. The process that makes an operating system safer by considering the default level obtained at the installation is known as hardening. Experience and technical knowledge are important attributes for the professional performing this process. In this context, automated rule-based tools are often used to assist professionals with little experience in vulnerability identification activities. However, the use of rules establishes a dependency on developers for the development of new rules as well as to keep them updated. Failure to update rules can significantly compromise the integrity of vulnerability identification results. In this paper, the Case-Based Reasoning (CBR) technique is used to improve tools that assist inexperienced professionals in conducting vulnerability identification activities. The purpose of using CBR is to make inexperienced professionals obtain similar results as experienced professionals. In addition, the dependence on rule developers is diminished. A prototype was developed considering the GNU/Linux system in order to carry out an experimental evaluation. This evaluation demonstrated that the application of CBR improves the performance of inexperienced professionals in terms of the number of identified vulnerabilities.
基于案例推理的GNU/Linux操作系统漏洞识别
多年来,操作系统安全性一直在稳步发展。已经开发了一些机制、软件和配置最佳实践指南,以提高此类系统的安全性。通过考虑安装时获得的默认级别使操作系统更安全的过程称为加固。经验和技术知识是执行此过程的专业人员的重要属性。在这种情况下,自动化的基于规则的工具通常用于帮助缺乏漏洞识别活动经验的专业人员。然而,规则的使用建立了对开发人员的依赖性,以开发新规则并使其保持更新。未能更新规则会严重损害漏洞识别结果的完整性。在本文中,使用基于案例的推理(CBR)技术来改进工具,帮助没有经验的专业人员进行漏洞识别活动。使用CBR的目的是使没有经验的专业人员获得与有经验的专业人员相似的结果。此外,减少了对规则开发人员的依赖。为了进行实验评估,开发了一个考虑GNU/Linux系统的原型。该评估表明,CBR的应用提高了经验不足的专业人员在识别漏洞数量方面的表现。
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