Cloud data secure deduplication scheme via role-based symmetric encryption by Jinbo XIONG, Yuanyuan ZHANG, Youliang TIAN, Zuobin YING, Qi LI, Rong MA

“…The rapid development of cloud computing and big data technology brings prople to enter the era of big data,more and more enterprises and individuals outsource their data to the cloud service providers.The explosive growth of data and data replicas as well as the increasing management overhead bring a big challenge to the cloud storage space.Meanwhile,some serious issues such as the privacy disclosure,authorized access,secure deduplication,rekeying and permission revocation should also be taken into account.In order to address these problems,a role-based symmetric encryption algorithm was proposed,which established a mapping relation between roles and role keys.Moreover,a secure deduplication scheme was proposed via role-based symmetric encryption to achieve both the privacy protection and the authorized deduplication under the hierarchical architecture in the cloud computing environment.Furthermore,in the proposed scheme,the group key agreement protocol was utilized to achieve rekeying and permission revocation.Finally,the security analysis shows that the proposed role-based symmetric encryption algorithm is provably secure under the standard model,and the deduplication scheme can meet the security requirements.The performance analysis and experimental results indicate that the proposed scheme is effective and efficient.…”
Get full text

Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit by Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

Get full text

ASD-YOLO: a lightweight network for coffee fruit ripening detection in complex scenarios by Baofeng Ye, Baofeng Ye, Renzheng Xue, Renzheng Xue, Haiqiang Xu, Haiqiang Xu

Get full text

Long-term survival with pemetrexed-based chemotherapy in a patient with metastatic lung adenocarcinoma of unclear primary origin harboring MTHFR C677T(T/T) mutation: a case report by Yuan Yu, Yuan Yu, Yuan Yu, Nan-Jing Li, Nan-Jing Li, Nan-Jing Li, Nan-Jing Li, Jin Wang, Jin Wang, Jin Wang, Jin Wang

Get full text

Ecological niche and phenotypic differences among two alpine Rhododendron species and their natural hybrids in a common landscape by Yanghui Zhao, Ying Zhang, Liang Xu, Yadan Yan, Chuncheng Wang, Yafeng Wen, Donglin Zhang

Get full text

Do the Effects of ICT Use on Trip Generation Vary across Travel Modes? Evidence from Beijing by Chaoying Yin, Xiaoquan Wang, Chunfu Shao

Get full text

Robust Fractional Low-Order Multiple Window STFT for Infinite Variance Process Environment by Haibin Wang, Changshou Deng, Junbo Long, Youxue Zhou

Get full text

Sepsis-Associated Acute Kidney Disease Incidence, Trajectory, and Outcomes by Hsiu-Yin Chiang, Chih-Chia Liang, Ya-Luan Hsiao, Uyen-Minh Le, Yi-Ching Chang, Pei-Shan Chen, David Ray Chang, I-Wen Ting, Hung-Chieh Yeh, Chin-Chi Kuo

Get full text

PAB-Mamba-YOLO: VSSM assists in YOLO for aggressive behavior detection among weaned piglets by Xue Xia, Ning Zhang, Zhibin Guan, Xin Chai, Shixin Ma, Xiujuan Chai, Tan Sun

Get full text

Application of Customer Segmentation for Electronic Toll Collection: A Case Study by Chao Qian, Meng Yang, Peiqi Li, Shuguang Li

“…Applying big data technology, this study presents a customer segmentation method of Electronic Toll Collection (ETC) based on vehicle behavioral characteristics. …”
Get full text

Cost-Effective Resource Provisioning for Real-Time Workflow in Cloud by Lei Wu, Ran Ding, Zhaohong Jia, Xuejun Li

“…In the era of big data, mining and analysis of the enormous amount of data has been widely used to support decision-making. …”
Get full text

A New Type of Eye Movement Model Based on Recurrent Neural Networks for Simulating the Gaze Behavior of Human Reading by Xiaoming Wang, Xinbo Zhao, Jinchang Ren

Get full text

An Approach for Discovering Urban Transport Service Problem Based on Hotline by Ruo-yu Wu, Chun-fu Shao, Cheng-xiang Zhuge, Xin-yi Wang, Xu-yang Yin

Get full text

Optimization of Bus Bridging Service under Unexpected Metro Disruptions with Dynamic Passenger Flows by Jiadong Wang, Zhenzhou Yuan, Yonghao Yin

Get full text

An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product by Siyuan Chen, Liangyun Liu, Lichun Sui, Xinjie Liu, Yan Ma

Get full text

Erratum to “Development and validation of machine learning based prediction model for postoperative pain risk after extraction of impacted mandibular third molars” [Heliyon 9(12),... by Dongsheng Yu, Zifeng Liu, Weijie Zhuang, Kechen Li, Yaxin Lu

Get full text

Automated Tomato Leaf Disease Detection Using Image Processing: An SVM-Based Approach with GLCM and SIFT Features by Rashid Khan, Nasir Ud Din, Asim Zaman, Bingding Huang

Get full text

Graph neural network driven traffic prediction technology:review and challenge by Yi ZHOU, Shuting HU, Wei LI, Nan CHENG, Ning LU, Xuemin(Sherman) SHEN

“…With the rapid development of Internet of things and artificial intelligence technology, accurate analysis and prediction of traffic data have become the primary target of intelligent transportations.In recent years, the method of traffic forecasting has gradually changed from the classical model-driven type to the data-driven type.However, how to effectively analyze the spatial-temporal characteristics of road networks through big data is one of the key issues in the traffic prediction process.Spatiotemporal big data analysis is a powerful tool for the traffic prediction.The traffic network can be modeled as a graph network, while the deep learning method can be extended on the graph network.Utilizing graph neural networks, we can build the spatiotemporal prediction model, and obtain the spatial-temporal correlation between the sensor nodes in road networks effectively by using graph convolution, which can significantly improve the accuracy of traffic prediction models.The traffic forecasting technology driven by graph neural networks was explored, and two kinds of traffic prediction models based on the analysis of deep spatial-temporal characteristics were extracted.The actual cases were analyzed and evaluated to discuss the technical advantages and key challenges of graph neural networks in the traffic prediction.The potential issues of graph neural network driven prediction mechanisms were also excavated.…”
Get full text

Investigation of Coal Preparation for Life Cycle by Using Building Information Modeling (BIM): A Case Study by Jian Chen, Da-Lin Guo, Xiao-Long Dong, Xiao-Bo Hou, Zhi-Feng Wang

“…In this paper, the kappa big data processing architecture is used to realize the integration and unification of stream data and batch data processing process. …”
Get full text

Development of an Autonomous Driving Path-Generation Algorithm for a Crawler-Type Ridge-Forming Robot by Joong-hee Han, Chi-ho Park

Get full text