Integrating predictive analytics and threat intelligence for proactive cyber defense in corporate networks

Sarat Kehinde Akinade *

Concordia University of Edmonton, Faculty of Information Technology, Edmonton, Alberta, Canada.
 
Research Article
International Journal of Science and Research Archive, 2023, 09(01), 855-859.
Article DOI: 10.30574/ijsra.2023.9.1.0419
Publication history: 
Received on 18 April 2023; revised on 21 June 2023; accepted on 28 June 2023
 
Abstract: 
Businesses today must contend with more sophisticated and rapidly evolving threats to their networks that require proactive, intelligence-based protective measures. This research analyzes how proactive enterprise environment detection, automated and semi-automated response actions, and prioritization are possible using predictive analytics alongside structured threat intelligence. It draws on NIST and MITRE standards, IBM X-Force, NTT, and Palo Alto Unit 42's Threat Reports, as well as contemporary research on predictive analytics for cyber threat intelligence to do (1) define an operational integration model, (2) create an organizational readiness assessment instrument, (3) create three synthesis tables that summarize readiness, benefits, and barriers based on an expert sample of 120 respondents, and (4) provide actionable phased adoption recommendations. This paper argues that with careful governance, the combination of predictive analytics and cyber threat intelligence aids in significantly improving prioritization and detection time and controversy over telemetry quality, predictive CTI operationalization (in MITRE ATT&CK framework), analytic expertise, and machine learning lifecycle governance are crucial.
 
Keywords: 
Predictive Analytics; Intelligence; Cyber Defence; Corporate Network
 
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0