riskAIchain: AI-Driven IT Infrastructure—Blockchain-Backed Approach for Enhanced Risk Management

Mir Mehedi Rahman, Bishwo Prakash Pokharel, Sayed Abu Sayeed, Sujan Kumar Bhowmik, Naresh Kshetri () and Nafiz Eashrak
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Mir Mehedi Rahman: School of Business & Technology, Emporia State University, Emporia, KS 66801, USA
Bishwo Prakash Pokharel: Sault College of Applied Arts and Technology, Marie, ON P6B 4J3, Canada
Sayed Abu Sayeed: College of Business, Florida Atlantic University, Boca Raton, FL 33431, USA
Sujan Kumar Bhowmik: Department of Statistics & Data Science, Jahangirnagar University, Savar 1342, Bangladesh
Naresh Kshetri: Department of Cybersecurity, Rochester Institute of Technology, Rochester, NY 14623, USA
Nafiz Eashrak: Department of Business & Technology Management, Islamic University of Technology, Gazipur 1704, Bangladesh

Risks, 2024, vol. 12, issue 12, 1-26

Abstract: In the evolving landscape of cybersecurity, traditional information technology (IT) infrastructures often struggle to meet the demands of modern risk management frameworks, which require enhanced security, scalability, and analytical capabilities. This paper proposes a novel artificial intelligence (AI)–driven IT infrastructure backed by blockchain technology, specifically designed to optimize risk management processes in diverse organizational environments. By leveraging artificial intelligence for predictive analytics, anomaly detection, and data-driven decision-making, combined with blockchain’s secure and immutable ledger for data integrity and transparency, the proposed infrastructure offers a robust solution to existing challenges in risk management. The infrastructure is adaptable and scalable to support a variety of risk management methodologies, providing a more secure, efficient, and intelligent system. The findings highlight significant improvements in the accuracy, speed, and reliability of risk management, underscoring the infrastructure’s capability to proactively address emerging cyber threats. To ensure the proposed model effectively addresses the most critical issues, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique will be used to analyze and evaluate the interrelationships among the existing critical factors. This approach evaluates the interrelationships and impacts of these factors, verifying the model’s comprehensiveness in managing organizational risk. This study lays the foundation for future research aimed at refining AI-driven infrastructures and exploring their broader applications in enhancing organizational cybersecurity.

Keywords: AI-driven infrastructure; AI in cybersecurity; DEMATEL; blockchain technology; organizational risk management; regression analysis; secure IT infrastructure (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
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