# Authentication and Authorization for Mobile IoT Devices using Bio-features: Recent Advances and Future Trends

## TL;DR

This paper reviews recent advances in using biometric features for authenticating mobile IoT devices, discussing challenges, methods, threat models, and future research directions.

## Contribution

It provides a comprehensive summary of biometric authentication schemes for mobile IoT devices, highlighting current challenges and future research trends.

## Key findings

- Analysis of physiological and behavioral biometric features
- Overview of machine learning methods used in authentication
- Identification of key challenges and future research directions

## Abstract

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.