A Holistic Approach for Insider Threat Assessment and Mitigation

Abstract

In recent times, insider threats have become one of the most complex and persistent cybersecurity challenges to manage, primarily because insiders are trusted and have legitimate access to organisational systems and data. Both public and private organisations face considerable risks of financial losses, data breaches, operational disruptions, and reputational damage resulting from malicious or negligent insiders. This study introduces the All-inclusive Threat and Organisational Mitigation (ATOM) Framework, a comprehensive and adaptable model designed to understand, detect, and mitigate insider risks through an integrated, layered, and structured approach. Unlike traditional strategies that focus narrowly on individual or technical factors, the ATOM framework aligns security measures with organisational objectives, governance policies, and regulatory compliance requirements. It emphasises proactive protection of sensitive digital assets and advocates a holistic approach that combines human behaviour analysis, technical monitoring, and organisational resilience. The framework provides practical tools and insights that assist organisations in anticipating, assessing, and counteracting insider threats more effectively. It also explores innovative analytical and technological methods to enhance detection, prevention, and response capabilities. The framework underscores the importance of proactive monitoring of human behaviours, vulnerabilities, and indicators of insider threats to close cybersecurity gaps and strengthen the resilience of critical systems and information. Additionally, the work is currently examining artificial intelligence (AI)-driven adaptive deception techniques that generate convincing fake data to mislead and monitor insider behaviour, while carefully considering associated ethical considerations.