Authentication and Authorization for Mobile IoT Devices using Bio-features: Recent Advances and Future Trends
It addresses security issues for IoT device users by summarizing existing research, but is incremental as it focuses on review and taxonomy.
This paper reviews biometric-based authentication and authorization schemes for mobile IoT devices, analyzing recent advances, threat models, and challenges, but does not present new experimental results or concrete numbers.
Bio-features are fast becoming a key tool to authenticate the IoT devices; in this sense, the purpose of this investigation is to summaries the factors that hinder biometrics models' development and deployment on a large scale, including human physiological (e.g., face, eyes, fingerprints-palm, or electrocardiogram) and behavioral features (e.g., signature, voice, gait, or keystroke). The different machine learning and data mining methods used by authentication and authorization schemes for mobile IoT devices are provided. Threat models and countermeasures used by biometrics-based authentication schemes for mobile IoT devices are also presented. More specifically, We analyze the state of the art of the existing biometric-based authentication schemes for IoT devices. Based on the current taxonomy, We conclude our paper with different types of challenges for future research efforts in biometrics-based authentication schemes for IoT devices.