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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http://dx.doi.org/10.3390/s24113575 | DOI Listing |
ACS Appl Mater Interfaces
January 2025
Key Laboratory of MEMS of the Ministry of Education, Southeast University, Nanjing 210096, China.
As one of the core parts of the Internet-of-things (IOTs), multimodal sensors have exhibited great advantages in fields such as human-machine interaction, electronic skin, and environmental monitoring. However, current multimodal sensors substantially introduce a bloated equipment architecture and a complicated decoupling mechanism. In this work we propose a multimodal fusion sensing platform based on a power-dependent piecewise linear decoupling mechanism, allowing four parameters to be perceived and decoded from the passive wireless single component, which greatly broadens the configurable freedom of a sensor in the IOT.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Electronic Engineering, BNRist/LFET, Tsinghua University, Beijing, China.
Physical unclonable functions (PUFs) are of immense potential in authentication scenarios for Internet of Things (IoT) devices. For creditable and lightweight PUF applications, key attributes, including low power, high reconfigurability and large challenge-response pair (CRP) space, are desirable. Here, we report a ferroelectric field-effect transistor (FeFET)-based strong PUF with high reconfigurability and low power, which leverages the FeFET cycle-to-cycle variation throughout the workflow and introduces charge-domain in-memory computing.
View Article and Find Full Text PDFPhys Chem Chem Phys
January 2025
School of Electronics and IoT, Chongqing Polytechnic University of Electronic Technology, Chongqing, China.
This study proposes a spin-valley electron beam splitter based on the inner-edge states in a topological-insulator junction, which can allocate different ratios of spin-valley current outputs. Since the inner-edge states are associated with the "nearest path selection" mechanism, this device is referred to as the interface-modulating spin-valley electron beam splitter. Additionally, two perfect spin-valley filters in similar topological-insulator junctions are established in this study.
View Article and Find Full Text PDFSci Rep
December 2024
School of Information Technology, Northwest University, Xi'an, 710127, Shaanxi, China.
Passive temperature sensing systems based on the Internet of Things (IoT) present an efficient, reliable, and convenient solution for temperature monitoring with extensive application prospects and market value. This paper introduces a passive, battery-free, chipless, metasurface temperature sensing tag. The key insight is that the sensing tag uses vanadium dioxide ([Formula: see text]) to solve the problems of measuring distance, large size, and high cost related to active devices.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Information Security, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.
In Internet of Things (IoT) networks, identifying the primary Medium Access Control (MAC) layer protocol which is suited for a service characteristic is necessary based on the requirements of the application. In this paper, we propose Energy Efficient and Group Priority MAC (EEGP-MAC) protocol using Hybrid Q-Learning Honey Badger Algorithm (QL-HBA) for IoT Networks. This algorithm employs reinforcement agents to select an environment based on predefined actions and tasks.
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