In smart applications, streaming IoT data is essential to building trust in sustainable IoT solutions. However, most existing systems for storing and disseminating IoT data streams lack reliability, security, and transparency, primarily due to centralized architectures that create single points of failure. To address these limitations, this research introduces TraVel, a blockchain and transfer learning-based framework for secure IoT data management. TraVel leverages decentralized IPFS storage to handle large data volumes effectively, integrating with a private Ethereum blockchain to enhance data integrity and accessibility. In the proposed scheme, the smart home ([Formula: see text]) data is collected securely and accessed over the BC with a unique hash key generated on the IPFS for all the files. Self-executing Ethereum smart contracts enforce access control and verify data integrity, allowing only validated, non-malicious data to be stored. An adversarial domain adaptation (DA) learning model is employed to detect and filter malicious data before it enters the blockchain. TraVel's performance is evaluated on blockchain parameters, with simulations conducted on REMIX IDE and InterPlanetary File System (IPFS), demonstrating its reliability and scalability for secure IoT data dissemination.
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http://dx.doi.org/10.1038/s41598-024-84837-8 | DOI Listing |
Sci Rep
January 2025
Torrens University Australia, Fortitude Valley, QLD 4006, Leaders Institute, 76 Park Road, Woolloongabba, QLD 4102, Brisbane, Queensland, Australia.
Sensors (Basel)
January 2025
College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China.
As the Internet of Things (IoT) expands globally, the challenge of signal transmission in remote regions without traditional communication infrastructure becomes prominent. An effective solution involves integrating aerial, terrestrial, and space components to form a Space-Air-Ground Integrated Network (SAGIN). This paper discusses an uplink signal scenario in which various types of data collection sensors as IoT devices use Unmanned Aerial Vehicles (UAVs) as relays to forward signals to low-Earth-orbit satellites.
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January 2025
Department of Instruction and Leadership, Duquesne University, Pittsburgh, PA 15282, USA.
This article examines how sensor technologies (such as environmental sensors, biometric sensors, and IoT devices) intersect with conversational AI models like ChatGPT 4.0. In particular, this article explores how data from different sensors in real time can improve AI models' comprehension of surroundings, user contexts, and physical conditions.
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January 2025
Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology, 50-370 Wrocław, Poland.
The distributed nature of IoT systems and new trends focusing on fog computing enforce the need for reliable communication that ensures the required quality of service for various scenarios. Due to the direct interaction with the real world, failure to deliver the required QoS level can introduce system failures and lead to further negative consequences for users. This paper introduces a prediction-based resource allocation method for Multi-Access Edge Computing-capable networks, aimed at assurance of the required QoS and optimization of resource utilization for various types of IoT use cases featuring adaptability to changes in users' requests.
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January 2025
School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.
The proliferation of the Internet of Things (IoT) has worsened the challenge of maintaining data and user privacy. IoT end devices, often deployed in unsupervised environments and connected to open networks, are susceptible to physical tampering and various other security attacks. Thus, robust, efficient authentication and key agreement (AKA) protocols are essential to protect data privacy during exchanges between end devices and servers.
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