Search Results - "IEEE transactions on network science and engineering"

A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems by Cai, Zhipeng, Zheng, Xu

“…To provide fine-grained access to different dimensions of the physical world, the data uploading in smart cyber-physical systems suffers novel challenges on…”
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TSMAE: A Novel Anomaly Detection Approach for Internet of Things Time Series Data Using Memory-Augmented Autoencoder by Gao, Honghao, Qiu, Binyang, Barroso, Ramon J. Duran, Hussain, Walayat, Xu, Yueshen, Wang, Xinheng

“…With the development of communication, the Internet of Things (IoT) has been widely deployed and used in industrial manufacturing, intelligent transportation,…”
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A Time-Dependent SIR Model for COVID-19 With Undetectable Infected Persons by Chen, Yi-Cheng, Lu, Ping-En, Chang, Cheng-Shang, Liu, Tzu-Hsuan

“…In this paper, we conduct mathematical and numerical analyses for COVID-19. To predict the trend of COVID-19, we propose a time-dependent SIR model that tracks…”
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PPSF: A Privacy-Preserving and Secure Framework Using Blockchain-Based Machine-Learning for IoT-Driven Smart Cities by Kumar, Prabhat, Kumar, Randhir, Srivastava, Gautam, Gupta, Govind P., Tripathi, Rakesh, Gadekallu, Thippa Reddy, Xiong, Neal N.

“…With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of urbanization. IoT networks allow distributed smart devices to…”
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Channel State Information Prediction for 5G Wireless Communications: A Deep Learning Approach by Luo, Changqing, Ji, Jinlong, Wang, Qianlong, Chen, Xuhui, Li, Pan

“…Channel state information (CSI) estimation is one of the most fundamental problems in wireless communication systems. Various methods, so far, have been…”
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CANintelliIDS: Detecting In-Vehicle Intrusion Attacks on a Controller Area Network Using CNN and Attention-Based GRU by Javed, Abdul Rehman, Rehman, Saif ur, Khan, Mohib Ullah, Alazab, Mamoun, G, Thippa Reddy

“…Controller area network (CAN) is a communication protocol that provides reliable and productive transmission between in-vehicle nodes continuously. CAN bus…”
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Edge Computing Driven Low-Light Image Dynamic Enhancement for Object Detection by Wu, Yirui, Guo, Haifeng, Chakraborty, Chinmay, Khosravi, Mohammad R., Berretti, Stefano, Wan, Shaohua

“…With fast increase in volume of mobile multimedia data, how to apply powerful deep learning methods to process data with real-time response becomes a major…”
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Towards Secure and Privacy-Preserving Data Sharing for COVID-19 Medical Records: A Blockchain-Empowered Approach by Tan, Liang, Yu, Keping, Shi, Na, Yang, Caixia, Wei, Wei, Lu, Huimin

“…COVID-19 is currently a major global public health challenge. In the battle against the outbreak of COVID-19, how to manage and share the COVID-19 Electric…”
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Privacy Protection of Medical Data Based on Multi-Scroll Memristive Hopfield Neural Network by Yu, Fei, Shen, Hui, Yu, Qiulin, Kong, Xinxin, Sharma, Pradip Kumar, Cai, Shuo

“…Memristive Hopfield neural network (MHNN) has complex dynamic behavior, which is suitable for encryption applications. In order to ensure the information…”
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Graph Neural Network-Driven Traffic Forecasting for the Connected Internet of Vehicles by Zhang, Qin, Yu, Keping, Guo, Zhiwei, Garg, Sahil, Rodrigues, Joel J. P. C., Hassan, Mohammad Mehedi, Guizani, Mohsen

“…Due to great advances in wireless communication, the connected Internet of vehicles (CIoVs) has become prevalent. Naturally, internal connections among active…”
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ContractWard: Automated Vulnerability Detection Models for Ethereum Smart Contracts by Wang, Wei, Song, Jingjing, Xu, Guangquan, Li, Yidong, Wang, Hao, Su, Chunhua

“…Smart contracts are decentralized applications running on Blockchain. A very large number of smart contracts has been deployed on Ethereum. Meanwhile, security…”
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Learning in the Air: Secure Federated Learning for UAV-Assisted Crowdsensing by Wang, Yuntao, Su, Zhou, Zhang, Ning, Benslimane, Abderrahim

“…Unmanned aerial vehicles (UAVs) combined with artificial intelligence (AI) have opened a revolutionized way for mobile crowdsensing (MCS). Conventional AI…”
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Deep Learning-Powered Vessel Trajectory Prediction for Improving Smart Traffic Services in Maritime Internet of Things by Liu, Ryan Wen, Liang, Maohan, Nie, Jiangtian, Lim, Wei Yang Bryan, Zhang, Yang, Guizani, Mohsen

“…The maritime Internet of Things (IoT) has recently emerged as a revolutionary communication paradigm where a large number of moving vessels are closely…”
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Many-Objective Deployment Optimization for a Drone-Assisted Camera Network by Cao, Bin, Li, Meng, Liu, Xin, Zhao, Jianwei, Cao, Wenxi, Lv, Zhihan

“…Drone-assisted camera networks can be used in many applications. However, different application requirements lead to different deployment scenarios. In this…”
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Blockchain-Enabled Authentication Handover With Efficient Privacy Protection in SDN-Based 5G Networks by Yazdinejad, Abbas, Parizi, Reza M., Dehghantanha, Ali, Choo, Kim-Kwang Raymond

“…5G mobile networks provide additional benefits in terms of lower latency, higher data rates, and more coverage, in comparison to 4G networks, and they are also…”
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Homomorphic Encryption-Based Privacy-Preserving Federated Learning in IoT-Enabled Healthcare System by Zhang, Li, Xu, Jianbo, Vijayakumar, Pandi, Sharma, Pradip Kumar, Ghosh, Uttam

“…In this work, the federated learning mechanism is introduced into the deep learning of medical models in Internet of Things (IoT)-based healthcare system…”
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Deep Convolutional Neural Networks for Indoor Localization with CSI Images by Wang, Xuyu, Wang, Xiangyu, Mao, Shiwen

“…With the increasing demand of location-based services, Wi-Fi based localization has attracted great interest because it provides ubiquitous access in indoor…”
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BinDaaS: Blockchain-Based Deep-Learning as-a-Service in Healthcare 4.0 Applications by Bhattacharya, Pronaya, Tanwar, Sudeep, Bodkhe, Umesh, Tyagi, Sudhanshu, Kumar, Neeraj

“…Electronic Health Records (EHRs) allows patients to control, share, and manage their health records among family members, friends, and healthcare service…”
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Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data by Wu, Hongda, Wang, Ping

“…Federated Learning (FL) is a distributed learning paradigm that enables a large number of resource-limited nodes to collaboratively train a model without data…”
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Dynamic Digital Twin and Federated Learning With Incentives for Air-Ground Networks by Sun, Wen, Xu, Ning, Wang, Lu, Zhang, Haibin, Zhang, Yan

“…The air-ground network provides users with seamless connections and real-time services, while its resource constraint triggers a paradigm shift from machine…”
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