Grant Front Osaka, Osaka, Japan
September 8–11, 2025
Call for Special Sessions
The evolution of smart cities is redefining urban infrastructure through the integration of intelligent systems in transportation, governance, healthcare, financial services, and public safety. At the core of these services lies biometric-based authentication and access control, enabling seamless, secure interactions between citizens and digital systems. However, current implementations primarily rely on centralised architectures, which aggregate and process biometric and identity data through centrally managed machine learning models. While centralisation simplifies system management, it introduces a range of critical security, privacy, and interoperability concerns. The reliance on centralised biometric repositories creates significant vulnerabilities, as evidenced by the exposure of over 1.1 billion biometric records in 2022 across multiple sectors. According to IBM’s 2023 Cost of a Data Breach Report, incidents involving biometric and personal data incur some of the highest costs, averaging $4.45 million per breach. Furthermore, a global survey conducted by Accenture revealed that 87% of citizens are concerned about the handling and storage of their biometric data within centralised systems, indicating a growing trust deficit.
From an architectural standpoint, centralised machine learning systems face limitations in cross-domain interoperability, scalability, and real-time responsiveness - capabilities that are essential for interconnected smart city ecosystems. Challenges such as data silos, inconsistent standards, latency in authentication processes, single points of failure, and regulatory compliance barriers further impede the effectiveness and resilience of these systems. These challenges collectively underscore the pressing need for a decentralised, privacy-preserving identity framework that enables secure, scalable, and interoperable biometric authentication. Emerging technologies such as blockchain and federated learning offer promising solutions by decentralising identity management, enhancing privacy through local data processing, and enabling cross-sector collaboration without compromising data sovereignty. This special session aims to address these challenges and explore cutting-edge research and practical implementations that leverage decentralized technologies to enhance the trust, transparency, and resilience of biometric systems in smart cities.
This special session aims to address these challenges and explore cutting-edge research and practical implementations that leverage decentralized technologies to enhance the trust, transparency, and resilience of biometric systems in smart cities. We invite original contributions and case studies addressing, but not limited to, the following themes:
Authors are invited to submit original research, case studies, and short papers through the main conference submission portal. Submissions should adhere to the formatting guidelines provided by the conference and will be peer-reviewed. For more details about the submission template and formating, please visit Submission Details
Accepted papers will be presented in the session and included in the official conference proceedings.