Enhancing Security in Ambient Intelligence: A STRIDE Threat Modeling Perspective

Ambient intelligence (AmI) systems, which create smart and adaptive environments, offer numerous benefits but raise significant security concerns. In this paper, we present a security analysis for ambient intelligence using the Stride threat modeling approach. STRIDE, an acronym for Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privilege, provides a systematic framework for identifying and mitigating threats in AmI environments. We focus on identifying and analyzing security risks specific to ambient intelligence systems, considering the unique characteristics and challenges they pose. By applying the STRIDE threat modeling approach, we uncover vulnerabilities and provide recommendations to enhance the security posture of various AmI components, such as sensors, data processing, communication channels, and user interactions. Furthermore, our research findings contribute to a better understanding of security issues in ambient intelligence and provide valuable insights for developers, system architects, and policymakers to design and deploy secure AmI systems.