Ubiquitous devices have become an integral part of everyday life, supporting interactions in both private and public contexts. As users engage with personal and shared devices, ensuring the privacy of these interactions remains critical. However, traditional methods often rely on explicit actions that disrupt user experience and are susceptible to observation, underscoring the need for seamless, implicit approaches.

Biometric-based methods, which leverage physiological and behavioral traits, offer robust and unobtrusive solutions for user identification. While these methods enable secure interactions, they remain vulnerable to impersonation attacks and behavioral drift and are influenced by dynamic environmental conditions. Addressing these challenges is essential to scaling biometric systems effectively across diverse devices, environments, and user scenarios.

This thesis investigates three core challenges hindering scalable biometric systems: (1) observation and impersonation attacks, including the impact of assistive visualization in mimicry; (2) the risks of deploying behavioral biometrics in uncontrolled public settings by understanding the influence of dynamic environmental factors on system performance; and (3) user understanding and perception of these systems, which affect their adoption and effectiveness.

To address these challenges, this work introduces two novel biometric identification methods that leverage emerging technologies. The first employs thermal imaging to capture foot-based characteristics and thermal traces for contactless user identification in smart environments. The second utilizes robotic arm sensors in collaborative robotic settings to implicitly identify users based on their unique gestures during direct interactions. These methods contribute to privacy-aware, continuous, and context-adaptive biometric identification across varied scenarios.

Beyond technical advancements, this thesis explores the broader implications of biometric adoption, focusing on user preferences, ethical considerations, and privacy challenges. It highlights the need to strike a balance between privacy and scalability while ensuring that emerging technologies, such as thermal imaging and collaborative robotics, align with societal expectations. Additionally, it examines how tensions between efficiency and transparency can be addressed to foster trust and support the widespread adoption of privacy-preserving biometric systems.