The Role of Natural Language Processing in Automating Cybersecurity Compliance Audits

Authors

  • Jane Smith Professor of Computer Science, University of Technology, London, UK Author

Keywords:

Natural Language Processing, Cybersecurity, Compliance Audits, Policy Validation, Automation, Cyber Threats

Abstract

The increasing complexity of cybersecurity infrastructures and the growing regulatory requirements in the digital space have made compliance audits a time-consuming and resource-intensive task. To address these challenges, Natural Language Processing (NLP) techniques have emerged as promising solutions for automating key aspects of cybersecurity compliance checks, including policy validation and audit reporting. This paper explores the application of NLP in cybersecurity audit automation, focusing on how NLP algorithms can efficiently process large volumes of policy documents, identify non-compliance risks, and generate actionable insights for security professionals. By analyzing case studies and recent research in the field, we discuss the accuracy, efficiency, and limitations of current NLP tools used in cybersecurity compliance. Furthermore, we examine the integration of NLP systems into broader cybersecurity frameworks and provide future research directions for enhancing their effectiveness.

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Published

19-09-2024

How to Cite

[1]
Jane Smith, “The Role of Natural Language Processing in Automating Cybersecurity Compliance Audits”, Distrib Learn Broad Appl Sci Res, vol. 10, pp. 360–366, Sep. 2024, Accessed: Nov. 06, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/163

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