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An Automated Framework for Cybersecurity Policy Compliance Assessment Against Security Control Standards

arXiv Security Archived May 11, 2026 ✓ Full text saved

arXiv:2605.07515v1 Announce Type: new Abstract: Organizational cybersecurity policies are often examined to determine whether they adequately comply standard security controls. This task is difficult because control statements are abstract, whereas policy documents describe governance practices in varied natural language. As a result, policy-based control assessment is time-consuming, difficult to standardize, and often difficult to document in a traceable manner. To address this gap, we present

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    Computer Science > Cryptography and Security [Submitted on 8 May 2026] An Automated Framework for Cybersecurity Policy Compliance Assessment Against Security Control Standards Bikash Saha, Sandeep Kumar Shukla Organizational cybersecurity policies are often examined to determine whether they adequately comply standard security controls. This task is difficult because control statements are abstract, whereas policy documents describe governance practices in varied natural language. As a result, policy-based control assessment is time-consuming, difficult to standardize, and often difficult to document in a traceable manner. To address this gap, we present PROPARAG, an audit support approach for evaluating organizational cybersecurity policies against security controls autonomously. For each control, the approach retrieves relevant policy evidence, assesses coverage, identifies missing elements, and generates supporting explanations and recommendations. We evaluate PROPARAG on two real-world organizational policy corpora using 1,007 NIST SP 800-53 controls across both closed-source and open-source large language models (LLMs). The framework achieves F1 scores of 88.54 on OrgA and 82.31 on OrgB. The evaluation also shows that PROPARAG identifies relevant gaps in documented organizational policies and generates grounded recommendations for each identified gap. This research provides foundation for LLM-powered autonomous control-level assessment of organizational cybersecurity policies. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.07515 [cs.CR]   (or arXiv:2605.07515v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.07515 Focus to learn more Submission history From: Bikash Saha [view email] [v1] Fri, 8 May 2026 09:45:25 UTC (2,275 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    May 11, 2026
    Archived
    May 11, 2026
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