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The Effectiveness of Cyber Threat Intelligence in Improving Security Operations

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  • Joshua Smallman

Abstract

The purpose of this research was to comprehensively evaluate the effectiveness of Cyber Threat Intelligence (CTI) in enhancing security operations, while simultaneously identifying the various barriers to its adoption. Additionally, the study aimed to provide potential solutions to mitigate the identified barriers, to ensure successful adoption of CTI.A systematic review was undertaken to identify the main factors of enhanced security operations. Relevant questions and statements were then developed from these factors and a questionnaire was created using Google Forms. These questionnaires were then distributed via email to a sample size of 50 information technology professionals. These results were then analyzed using Microsoft Excel and SPSS. Overall, the research revealed that companies who used CTI reported significant gains in threat detection and response, risk management and threat-hunting abilities, which in turn lead to enhanced security operations. According to the research, several factors prevented organizations from adopting CTI. Among these were technological, regulatory, ignorance-related, and lack of executive support. Finally, to tackle these identified barriers the following were proposed adopting comprehensive awareness and education programs, the formation of an Executive CTI Steering Committees, structured CTI training and skills development programs, technology assessment and modernization initiative-based initiatives, proactive compliance, and legal strategies.

Suggested Citation

  • Joshua Smallman, 2024. "The Effectiveness of Cyber Threat Intelligence in Improving Security Operations," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 5(1), pages 189-209.
  • Handle: RePEc:das:njaigs:v:5:y:2024:i:1:p:189-209:id:193
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    1. Snyder, Hannah, 2019. "Literature review as a research methodology: An overview and guidelines," Journal of Business Research, Elsevier, vol. 104(C), pages 333-339.
    2. Akanksha. A. Kherdikar-Kurlekar & Anusuya S., 2011. "A Study on Role of Data Mining in Research Methodology," Indian Journal of Commerce and Management Studies, Educational Research Multimedia & Publications,India, vol. 2(3), pages 22-30, March.
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    Cited by:

    1. Harsh Daiya, 2024. "AI-Driven Risk Management Strategies in Financial Technology," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 5(1), pages 194-216.

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