Evaluative Study of Recent Developments in Secure Mobile and Biometric Authentication for IoT Infrastructure

Abstract

The exponential growth and integration of Internet of Things (IoT) technologies across personal, commercial, and industrial domains have fundamentally reshaped the cybersecurity landscape, ushering in a critical need for advanced, seamless, and resilient authentication frameworks. Conventional authentication mechanisms—such as alphanumeric passwords and personal identification numbers (PINs)—are increasingly regarded as obsolete due to their susceptibility to brute-force attacks, poor usability, and inadequate protection against sophisticated intrusion techniques in distributed IoT infrastructures.

In response, biometric authentication—particularly when deployed through mobile platforms— has gained traction as a next-generation solution offering high assurance identity verification grounded in unique physiological and behavioral traits. Its potential for frictionless, continuous, and context-aware authentication makes it especially suitable for heterogeneous and real-time IoT environments. This chapter provides a holistic and critical review of contemporary literature published between 2021 and 2025, addressing how mobile-biometric systems are being integrated into IoT ecosystems to fortify digital identity assurance.

The review synthesizes eight prominent research directions, including multimodal biometric fusion leveraging deep learning, decentralized intelligence through AI at the edge, sensor miniaturization for wearable authentication, privacy-enhancing computation models, and blockchain-facilitated identity decentralization. These developments are examined through a set of standardized performance metrics—such as True Acceptance Rate (TAR), False Acceptance Rate (FAR), system latency, energy efficiency, and interoperability across platforms—to assess their readiness for real-world application.

Despite considerable advancements, the analysis underscores several unresolved challenges. Chief among these are the absence of cross-platform standards for biometric data formats, computational bottlenecks on energy-constrained IoT nodes, unresolved ethical and legal considerations surrounding biometric data governance, and increasing vulnerability to adversarial attacks such as synthetic identity fabrication and deepfakes. Ultimately, the chapter argues for a coordinated, interdisciplinary research agenda focused on engineering adaptive, privacy-centric, and legally compliant authentication architectures that are capable of securing the future trajectory of smart, interconnected environments.