EduRSS: A Blockchain-Based Educational Records Secure Storage and Sharing Scheme

Zhang, Lipeng; Han, Dong‐Guk

doi:10.1109/access.2019.2956157

Cited by 108 publications

(71 citation statements)

References 26 publications

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“…The DEIDV-Hop algorithm is compared with DV-Hop, PSODV-Hop [43], and GSODV-Hop [44] through simulation implemented on MATLAB 2014a [45], running on a desktop PC with one Intel(R) Core(TM) i5-6500 CPU @3.20 GHz processor, 8 GB RAM, and Windows 7 OS.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Han

et al. 2020

Sensors

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The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Han

et al. 2020

Sensors

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“…Compared with the existing method MCAN, DCAN can make use of the complex correlation between multimodal features in a more effective way and extract more discriminative features for images and questions. This exploration of modeling dense intra- and inter-modality interactions has been applied to intelligent transportation [ 42 ], intelligent robot [ 43 ], and other fields [ 44 , 45 , 46 ]. Applying it to a wider range of scenarios will be an inevitable trend in the future.…”

Section: Discussionmentioning

confidence: 99%

An Effective Dense Co-Attention Networks for Visual Question Answering

Han

2020

Sensors

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At present, the state-of-the-art approaches of Visual Question Answering (VQA) mainly use the co-attention model to relate each visual object with text objects, which can achieve the coarse interactions between multimodalities. However, they ignore the dense self-attention within question modality. In order to solve this problem and improve the accuracy of VQA tasks, in the present paper, an effective Dense Co-Attention Networks (DCAN) is proposed. First, to better capture the relationship between words that are relatively far apart and make the extracted semantics more robust, the Bidirectional Long Short-Term Memory (Bi-LSTM) neural network is introduced to encode questions and answers; second, to realize the fine-grained interactions between the question words and image regions, a dense multimodal co-attention model is proposed. The model’s basic components include the self-attention unit and the guided-attention unit, which are cascaded in depth to form a hierarchical structure. The experimental results on the VQA-v2 dataset show that DCAN has obvious performance advantages, which makes VQA applicable to a wider range of AI scenarios.

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“…In reference [21], the Fair-Access privacy protection and rights management framework was proposed, which used smart contracts to manage access policies in a fine-grained way and checked policy reuse. In reference [22], a scheme named EduRSS was proposed. It used a Ethereumbased blockchain to store and share educational records.…”

Section: Related Workmentioning

confidence: 99%

Fabric-iot: A Blockchain-Based Access Control System in IoT

2020

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IoT devices have some special characteristics, such as mobility, limited performance, and distributed deployment, which makes it difficult for traditional centralized access control methods to support access control in current large-scale IoT environment. To address these challenges, this paper proposes an access control system in IoT named fabric-iot, which is based on Hyperledger Fabric blockchain framework and attributed based access control (ABAC). The system contains three kinds of smart contracts, which are Device Contract (DC), Policy Contract (PC), and Access Contract (AC). DC provides a method to store the URL of resource data produced by devices, and a method to query it. PC provides functions to manage ABAC policies for admin users. AC is the core program to implement an access control method for normal users. Combined with ABAC and blockchain technology, fabric-iot can provide decentralized, fine-grained and dynamic access control management in IoT. To verify the performance of this system, two groups of simulation experiments are designed. The results show that fabric-iot can maintain high throughput in largescale request environment and reach consensus efficiently in a distributed system to ensure data consistency.

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EduRSS: A Blockchain-Based Educational Records Secure Storage and Sharing Scheme

Cited by 108 publications

References 26 publications

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

An Effective Dense Co-Attention Networks for Visual Question Answering

Fabric-iot: A Blockchain-Based Access Control System in IoT

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