Zero Trust and Predictive Security in Business Intelligence Architectures
Maen Marwan Alzubi, Mohammad Almseidin, Mouhammd Sharari Alkasassbeh, Murad Bashabsheh, Jamil Al‐Sawwa, Ashraf S. Mashaleh · 2025
In recent years, business intelligence architecture has faced mounting challenges in ensuring data confidentiality, integrity, and availability. Traditional perimeter-based security approaches increasingly fail to address sophisticated threats within evolving enterprise environments. To bridge this critical gap, zero trust frameworks combined with predictive security models offer a transformative direction for securing complex business intelligence ecosystems. This chapter explores theoretical foundations of zero trust architecture, predictive analytics, and their synergy in business intelligence contexts. Findings reveal that integrating adaptive authentication, AI-driven anomaly detection, and granular access control enhances resilience against advanced threats. The discussion highlights how predictive models anticipate breaches, allowing proactive mitigation strategies. The chapter concludes by emphasizing the strategic value of zero trust and predictive security integration for safeguarding data-driven decision-making processes in contemporary enterprises.