Access Control, Key Management, and Trust for Emerging Wireless Body Area Networks

Salehi Shahraki, Ahmad; Lauer, Hagen; Grobler, Marthie; Sakzad, Amin; Rudolph, Carsten

doi:10.3390/s23249856

Cited by 6 publications

(1 citation statement)

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“…The primary factors for MFA are passwords, biometrics, and smart devices. Legitimate users are predicted from two-factor authentication whose constraints are PUF with location information [ 11 ]. Location is predicted from two signal characteristics: the signal strength indicator (RSSI), and the link quality indicator (LQI).…”

Section: Introductionmentioning

confidence: 99%

Two-Layered Multi-Factor Authentication Using Decentralized Blockchain in an IoT Environment

Bamashmos,

Chilamkurti,

Shahraki

2024

Sensors

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Internet of Things (IoT) technology is evolving over the peak of smart infrastructure with the participation of IoT devices in a wide range of applications. Traditional IoT authentication methods are vulnerable to threats due to wireless data transmission. However, IoT devices are resource- and energy-constrained, so building lightweight security that provides stronger authentication is essential. This paper proposes a novel, two-layered multi-factor authentication (2L-MFA) framework using blockchain to enhance IoT devices and user security. The first level of authentication is for IoT devices, one that considers secret keys, geographical location, and physically unclonable function (PUF). Proof-of-authentication (PoAh) and elliptic curve Diffie–Hellman are followed for lightweight and low latency support. Second-level authentication for IoT users, which are sub-categorized into four levels, each defined by specific factors such as identity, password, and biometrics. The first level involves a matrix-based password; the second level utilizes the elliptic curve digital signature algorithm (ECDSA); and levels 3 and 4 are secured with iris and finger vein, providing comprehensive and robust authentication. We deployed fuzzy logic to validate the authentication and make the system more robust. The 2L-MFA model significantly improves performance, reducing registration, login, and authentication times by up to 25%, 50%, and 25%, respectively, facilitating quicker cloud access post-authentication and enhancing overall efficiency.

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Section: Introductionmentioning

confidence: 99%