Showing papers in "Computer Standards & Interfaces in 2022"

TL;DR: In this paper, the q-rung orthopair fuzzy-weighted zero-inconsistency (q-ROFWZIC) method was extended with q-ROFDOSM, which was used in a case study regarding the MCDM problem of coronavirus disease 2019 (COVID-19) vaccine distribution.

TL;DR: In this paper , the q-rung orthopair fuzzy-weighted zero-inconsistency (q-ROFWZIC) method was extended with q-ROFDOSM, which was used in a case study regarding the MCDM problem of coronavirus disease 2019 (COVID-19) vaccine distribution.

TL;DR: A detailed security analysis and comparative study reveal that the proposed AKMS-AgriIoT supports better security, and provides more functionality features, less communication costs and comparable computation costs as compared to other relevant schemes.

TL;DR: In this article, the authors proposed a blockchain-based secure storage and sharing scheme for Electronic Learning Records (ELRs) in MOOCs learning systems, which can support efficient conditional anonymity, secure storage, and sharing without the need for sophisticated cryptographic calculations.

TL;DR: This work was partially supported by the Spanish Ministry of Science and Innovation and the European Regional Development Fund (ERDF) and project FAME and excellence network RCIS.

TL;DR: A secure distributed data storage scheme is proposed, which can be used in blockchain enabled edge computing and can be executed with low computational cost, which is practical for IOT environment in blockchainenabled edge computing.

TL;DR: In this article , a new authentication and key management scheme for IoT-enabled Intelligent Precision Agriculture (IPA), called AKMS-AgriIoT, has been put forward with the private blockchain-based solution.

TL;DR: Simulation results show that the proposed DOA tracking takes lesser time for tracking the current location of the drone target as opposed to conventional DOA estimation methods and it is observed that the tracking process remains unaffected by SNR.

TL;DR: Performance and security comparisons show that proposed scheme completes a cycle of authentication with a slight increase in computation time, but it offers all the required security features as compared with the scheme of Wazid et al.

TL;DR: An adaptive particle swarm optimization (PSO) ensemble with genetic mutation-based routing is proposed to select control nodes for IoT based software-defined WSN and the simulation result of the proposed algorithm outperforms over other algorithms under the different arrangements of the network.

TL;DR: In this paper , the authors propose an architecture for managing the resources of each tier: edge, fog and cloud, and demonstrate the proposed architecture through a case study of respiratory disease surveillance in hospitals.

TL;DR: In this paper , the authors proposed a low computational complexity subspace tracking algorithm for tracking the Direction of Arrival (DOA) of the intended target in order to provide seamless connectivity.

TL;DR: In this paper , the authors proposed the Moth-Flame Optimization-based secure scheme for RPL (MFO-RPL) to optimize the routing process and rank attack detection in RPL.

TL;DR: Wang et al. as mentioned in this paper proposed a novel secure arrangement method based on matrix eigenvalue calculation, which is more robust and efficient, which drives the proposed scheme to be more suitable for repeated aggregation.

TL;DR: This work constructs a generic server-aided secure multi-party computation protocol that can provide security guarantee in the setting where at most n-1 client parties are malicious while the server is semi-honest and there is no collusion between the server and clients.

TL;DR: In this paper , the authors propose a fully reusable microservice architecture, standardized through the use of the Web of things paradigm, with high efficiency in real-time data processing, supported by complex event processing techniques.

TL;DR: In this article , an adaptive particle swarm optimization (PSO) ensemble with genetic mutation-based routing is proposed to select control nodes for IoT based software-defined WSNs, which plays a significant role in selecting the control nodes by considering energy and distance parameters.

TL;DR: Wang et al. as mentioned in this paper proposed a novel secure arrangement method based on matrix eigenvalue calculation, which is more robust and efficient, which drives the proposed scheme to be more suitable for repeated aggregation.

TL;DR: This work proposes a privacy-preserving Byzantine-robust federated learning scheme (PBFL) which takes both the robustness of federatedLearning and the privacy of the workers into account and proves that the scheme provides a higher level of privacy protection compared to the previous Byzantine- Robust Federated learning algorithms.

TL;DR: Zhang et al. as discussed by the authors proposed a more aggressive algorithm for generating adversarial examples, namely, the accelerated gradient iterative fast gradient sign method(AI-FGSM), and proved that AI-FG SM can improve the transferability of adversarial example.

TL;DR: Wang et al. as discussed by the authors proposed a combination of non-interactive zero-knowledge proof and multi-signature with public key aggregation to preserve the full-fledged privacy protection property with a lower computational cost.

TL;DR: Wang et al. as mentioned in this paper proposed a generic server-aided secure multi-party computation protocol to solve the problem of secure collaborative computation in cloud computing, where at most n-1 client parties are malicious while the server is semi-honest and there is no collusion between the server and clients.

TL;DR: Wang et al. as discussed by the authors proposed a privacy-preserving federated learning scheme that is based on the cryptographic primitive of homomorphic re-encryption, which can protect user data and train user data through batch gradient descent.

TL;DR: Wang et al. as discussed by the authors designed a novel authentication data structure, namely, number-rank-based Merkle hash tree (NR-MHT), which can achieve data dynamic operations.

TL;DR: Wang et al. as mentioned in this paper proposed blockchain-based verifiable privacy-preserving data classification protocol (VeriDC) for medical data, which makes the data center check the classification result without involving an auditor.

TL;DR: Wang et al. as discussed by the authors proposed a privacy-preserving Byzantine-robust federated learning scheme (PBFL), which combines distributed Paillier encryption and zero-knowledge proof to guarantee privacy and filter out anomalies from Byzantine adversaries.

TL;DR: In this paper , a designated cloud server-based multi-user certificateless authenticated encryption with conjunctive keyword search (dmCLPAECKS) scheme was proposed, which does not require a secure channel between the designated Cloud server and a data receiver and provides security against keyword guessing attack.

TL;DR: Wang et al. as discussed by the authors proposed a privacy-preserving federated learning scheme that is based on the cryptographic primitive of homomorphic re-encryption, which can protect user data and train user data through batch gradient descent.

TL;DR: Wang et al. as mentioned in this paper proposed an indoor plane detection method based on space decomposition and an optimized random sample consensus (RANSAC) algorithm, in which the weighted PCA method is exploited to estimate the normal vector from point cloud, and angular clustering is employed to divide the interior space for obtaining the building components.

TL;DR: Wang et al. as mentioned in this paper proposed a new searchable algorithm based on LSSS (Linear Secret Sharing Scheme) access policy, which is superior to previous work in computational and storage efficiency.