Saudi Cultural Missions Theses & Dissertations
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Item Restricted Assessing the Extent of use of Biometric Technologies(Saudi Digital Library, 2025) Almutairi, Hissah; Furnell, StevenIn light of the accelerating digital transformation, biometric authentication systems have become a key component in enhancing digital security, especially given the shortcomings of traditional methods. This study examines the evolution of technologies such as facial and fingerprint recognition within Internet of Things (IoT) devices, analyzing market trends and user perceptions. The results show that some technologies are widely used because they are simple to incorporate into everyday devices, whereas newer innovations like iris or palm recognition are rarely used because of cultural and technical challenges. Due to issues with reliability and general concerns about data security, users show limited trust in these systems. Applications vary by industry. For example, biometrics are incorporated into luxury cars to improve security and also used in healthcare devices to precisely monitor health conditions. Along with the requirement to increase transparency in data processing, the technologies have to find a balance between security guarantees and convenience. In an age where technology influence every aspect of everyday life, the study suggests developing clear regulatory frameworks and encouraging collaboration between sectors to guarantee widespread and safe adoption while protecting user rights.14 0Item Restricted DEEP LEARNING MODELS FOR MOBILE AND WEARABLE BIOMETRICS(Saudi Digital Library, 2023-04-27) Almadan, Ali; Rattani, AjitaThe mobile technology revolution has transformed mobile devices from communication tools to all-in-one platforms. As a result, more people are using smartphones to access e-commerce and banking services, replacing traditional desktop computers. However, smartphones are more prone to being lost or stolen, requiring e ective user authentication mechanisms for securing transactions. Ocular biometrics o ers accuracy, security, and ease of use on mobile devices for user authentication. In addition, face recognition technology has been widely adopted in intelligence gathering, law enforcement, surveillance, and consumer applications. This technology has recently been implemented in smartphones and body-worn cameras (BWC) for surveillance and situational awareness. However, these high-performing models require significant computational resources, making their deployment on resource-constrained smartphones challenging. To address this challenge, studies have proposed compact-size ocular-based deep-learning models for on-device deployment. In this context, we conduct a thorough analysis of existing neural network compression techniques applied standalone and in combination for ocular-based user authentication and facial recognition.17 0