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- Title
CYBERSECURITY ANALYTICS: LEVERAGING BUSINESS ANALYTICS IN INDUSTRY 4.0 SETTINGS.
- Authors
WOLNIAK, Radosław
- Abstract
Purpose: The purpose of this publication is to present the applications of usage of business analytics in cybersecurity analytics. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of business analytics into cybersecurity practices within Industry 4.0 signifies a pivotal advancement in safeguarding organizational assets against the evolving cyber threat landscape. As industrial systems grow more complex and interconnected, traditional security methods focused on perimeter defenses are increasingly inadequate. Modern cybersecurity strategies must therefore incorporate advanced analytics to manage and mitigate risks effectively. Business analytics enhances cybersecurity through sophisticated machine learning algorithms, predictive capabilities for anticipating future threats, and improved incident response via real-time monitoring and automated alerts. These innovations foster a proactive and efficient security approach, enabling swift detection, response, and informed decision-making based on thorough risk assessments. Despite these advantages, challenges such as data overload, false positives, integration hurdles, and the need for specialized expertise persist. Additionally, concerns about data privacy, costs, and analytical complexity must be managed. Embracing business analytics while addressing these challenges will enable organizations to fortify their security posture, optimize resource use, and adapt to the demands of Industry 4.0, thereby shaping the future of cybersecurity in a rapidly evolving digital landscape. Originality/Value: Detailed analysis of all subjects related to the problems connected with the usage of business analytics in the case of cybersecurity analytics.
- Subjects
BUSINESS analytics; INTERNET security laws; INDUSTRY 4.0; MACHINE learning; INTERNET security; DATA privacy
- Publication
Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie, 2024, Issue 198, p619
- ISSN
1641-3466
- Publication type
Article
- DOI
10.29119/1641-3466.2024.198.35