| 1. |
- Li, Chao, et al.
(författare)
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Federated Hierarchical Trust-based Interaction Scheme for Cross-domain Industrial IoT
- 2023
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662 .- 2372-2541. ; 10:1, s. 447-457
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Tidskriftsartikel (refereegranskat)abstract
- The Industrial Internet of Things (IIoT) is considered to be one of the most promising revolutionary technologies to increase productivity. With the refined development of manufacturing, the entire manufacturing process is split up into several areas of IoT production. Devices from different domains cooperate to perform the same task, which cause security problems in interacted communication among them. Existing authentication methods cause heavy key management overhead or rely on a trusted third party. It is imperative to protect privacy and ensure the credibility of the device during device interaction. This paper proposes a federated hierarchical trust interaction scheme (FHTI) for the cross-domain industrial IoT. It builds a low-privacy network platform through blockchain and protects the data privacy of the IIoT. A hierarchical trust mechanism based on federated detection is designed to realize the unified trust evaluation of cross-domain devices. A trusted cross-domain method based on device trust value is designed to ensure the security and trustworthiness of cross-domain devices. The simulation results show that the FHTI scheme can improve the speed of identity authentication and the detection accuracy of malicious devices.
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| 2. |
- Luo, Yifei, et al.
(författare)
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Technology Roadmap for Flexible Sensors
- 2023
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Ingår i: ACS Nano. - : American Chemical Society. - 1936-0851 .- 1936-086X. ; 17:6, s. 5211-5295
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Forskningsöversikt (refereegranskat)abstract
- Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.
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| 3. |
- Yang, Hui, et al.
(författare)
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BrainIoT : Brain-Like Productive Services Provisioning with Federated Learning in Industrial IoT
- 2022
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 9:3, s. 2014-2024
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Tidskriftsartikel (refereegranskat)abstract
- The Industrial Internet of Things (IIoT) accommodates a huge number of heterogeneous devices to bring vast services under a distributed computing scenarios. Most productive services in IIoT are closely related to production control and require distributed network support with low delay. However, the resource reservation based on gross traffic prediction ignores the importance of productive services and treats them as ordinary services, so it is difficult to provide stable low delay support for large amounts of productive service requests. For many productions, unexpected communication delays are unacceptable, and the delay may lead to serious production accidents causing great losses, especially when the productive service is security related. In this article, we propose a brain-like productive service provisioning scheme with federated learning (BrainIoT) for IIoT. The BrainIoT scheme is composed of three algorithms, including industrial knowledge graph-based relation mining, federated learning-based service prediction, and globally optimized resource reservation. BrainIoT combines production information into network optimization, and utilizes the interfactory and intrafactory relations to enhance the accuracy of service prediction. The globally optimized resource reservation algorithm suitably reserves resources for predicted services considering various resources. The numerical results show that the BrainIoT scheme utilizes interfactory relation and intrafactory relation to make an accurate service prediction, which achieves 96% accuracy, and improves the quality of service.
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