Internet of things (IoT) is a technology that can collect the data sensed by the devices for the further real-time services. Using the technique of cloud computing to assist IoT devices in data storing can eliminate the disadvantage of the constrained local storage and computing capability. However, the complex network environment makes cloud servers vulnerable to attacks, and adversaries pretend to be legal IoT clients trying to access the cloud server. Hence, it is necessary to provide a mechanism of mutual authentication for the cloud system to enhance the storage security. In this paper, a secure mutual authentication is proposed for cloud-assisted IoT. Note that the technique of chameleon hash signature is used to construct the authentication. Moreover, the proposed scheme can provide storage checking with the assist of a fully-trusted entity, which highly improves the checking fairness and efficiency. Security analysis proves that the proposed scheme in this paper is correct. Performance analysis demonstrates that the proposed scheme can be performed with high efficiency.
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http://dx.doi.org/10.3934/mbe.2022514 | DOI Listing |
Sensors (Basel)
January 2025
School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
The Internet of Vehicles (IoV), a key component of smart transportation systems, leverages 5G communication for low-latency data transmission, facilitating real-time interactions between vehicles, roadside units (RSUs), and sensor networks. However, the open nature of 5G communication channels exposes IoV systems to significant security threats, such as eavesdropping, replay attacks, and message tampering. To address these challenges, this paper proposes the Efficient Cluster-based Mutual Authentication and Key Update Protocol (ECAUP) designed to secure IoV systems within 5G-enabled sensor networks.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64700, Nuevo Leon, Mexico.
With recent significant advancements in artificial intelligence, the necessity for more reliable recognition systems has rapidly increased to safeguard individual assets. The use of brain signals for authentication has gained substantial interest within the scientific community over the past decade. Most previous efforts have focused on identifying distinctive information within electroencephalogram (EEG) recordings.
View Article and Find Full Text PDFFront Health Serv
December 2024
University of British Columbia, Vancouver, BC, Canada.
This perspective article shares the viewpoints of two long-standing patient safety advocates who have participated first-hand in the evolution of patient engagement in healthcare quality and safety. Their involvement is motivated by a rejection of the common cruelty of institutional betrayal that compounds harm when patient safety fails. The advocates have sought to understand how it can be that fractured trust spreads so predictably after harm, just when it most needs strengthening.
View Article and Find Full Text PDFCogn Neurodyn
December 2024
Centre for Theoretical Neuroscience, University of Waterloo, 200 University Ave., Waterloo, ON N2L 3G1 Canada.
Distributed vector representations are a key bridging point between connectionist and symbolic representations in cognition. It is unclear how uncertainty should be modelled in systems using such representations. In this paper we discuss how bundles of symbols in certain Vector Symbolic Architectures (VSAs) can be understood as defining an object that has a relationship to a probability distribution, and how statements in VSAs can be understood as being analogous to probabilistic statements.
View Article and Find Full Text PDFPeerJ Comput Sci
October 2024
Department of Artificial Intelligence (AI) and Data Science, Sejong University, Seoul, Republic of South Korea.
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