TL;DR
This paper presents an automated approach using NLP to extract and implement security configurations for Windows from public guides, significantly reducing manual effort and increasing accuracy in system hardening.
Contribution
The authors develop a novel method combining NLP and Windows Administrative Templates to automatically extract and verify security rules from guides, achieving high implementation accuracy.
Findings
83% rules automatically implemented without manual effort
96% rules implemented with minimal manual effort
97% of rules correctly implemented across multiple guides
Abstract
Hardening is the process of configuring IT systems to ensure the security of the systems' components and data they process or store. The complexity of contemporary IT infrastructures, however, renders manual security hardening and maintenance a daunting task. In many organizations, security-configuration guides expressed in the SCAP (Security Content Automation Protocol) are used as a basis for hardening, but these guides by themselves provide no means for automatically implementing the required configurations. In this paper, we propose an approach to automatically extract the relevant information from publicly available security-configuration guides for Windows operating systems using natural language processing. In a second step, the extracted information is verified using the information of available settings stored in the Windows Administrative Template files, in which the…
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