AI-Driven Threat Modeling
C. V. Suresh Babu, Albert Gururaja V. · 2025
This chapter explores the integration of AI-driven threat modeling and risk assessment within software development to enhance security practices. Utilizing a comprehensive literature review, case studies, and qualitative interviews with industry professionals, the study identifies best practices and emerging trends in threat modeling methodologies such as STRIDE and DREAD. Key findings reveal that organizations adopting AI technologies experience improved threat detection and response times, leading to a more robust security posture. However, the study also highlights the importance of human oversight and the ethical considerations surrounding AI applications. The conclusions emphasize that a proactive approach, involving cross-functional teams and continuous adaptation to evolving cyber threats, is essential for building resilient software applications. This work underscores the significance of integrating AI into threat modeling as a critical strategy for organizations aiming to safeguard their digital assets.