Knowledge management and technology for enhanced cybersecurity effectiveness

Abstract

Cybersecurity continues to be a major concern and presents significant challenges for businesses, governments, nonprofits, and individuals. Organizations are working diligently to mitigate threats to these entities while the rate of cybercrime continues to increase in sophistication and reach. Current models in cybersecurity are becoming increasingly ineffective against the velocity, agility, and persistence of cyber adversaries. This challenge presents an opportunity to consider concepts and methods in knowledge management to strategically evaluate and prioritize adversarial cyber threat activities. This research aims to explore a conceptual framework designed to provide cybersecurity professionals with new models for knowledge management to increase the effectiveness of the detection, mitigation, and attribution of these threats. This conceptual approach draws from the literature on knowledge management and cybersecurity to integrate key concepts into a new theoretical framework. This paper presents a new hybrid model for cybersecurity that integrates core concepts of the classic Nonaka and Takeuchi Knowledge Spiral and the National Institute of Standards and Technology (NIST) Cybersecurity Framework augmented with emerging artificial intelligence and machine learning technologies. The development of a hybrid cybersecurity model combined with proven knowledge management strategies for continual knowledge creation and innovation represents an integrative model designed to address emerging cybersecurity challenges.