数字农科院2.0

B-FLACS: blockchain-based flexible lightweight access control scheme for data sharing in cloud

文献类型: 外文期刊

作者: Tao, Qi;Cui, Xiaohui

作者机构:

关键词: Lightweight;Flexible access control;Data security;Digital forensic;Blockchain

期刊名称: CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS

ISSN: 1386-7857

年卷期: 2022 年

页码:

收录情况: SCIE(2022版) ; ; EI(2022版)

摘要: Cloud storage provides convenience for data owners. But it faces serious challenges from data tampering and abuse. Flexible access control method is an effective way to protect shared data security. Existing attribute-based access control methods attempt to improve the access flexibility and security of shared data. But there are some problems for resourcelimited lightweight devices as performance and security to be solved. Blockchain can construct a trusted network for data owner to deal with data validity and digital forensics. This paper proposes a novel blockchain-based lightweight access control scheme. The proposed scheme uses blockchain to construct a trusted sharing network by consensus mechanism. The lightweight attribute-based sharing scheme is used to support fine-grained access control of data. In this scheme, it obfuscates the access control policy with fuzzy attribute set to improve system security, and reduces the computing complexity of system users by outsourcing complex operations to semi-trusted proxy servers. The security analysis shows that the scheme is ((S, rho), n - 1, epsilon)-secure against collusion attack between users and attribute authorities. The performance analysis results show that the proposed scheme reduces the computational complexity of user devices and provides faster response time compared with benchmark and state-of-the-art technologies.

分类号:

  • 相关文献

[1]Highly Secure In Vivo DNA Data Storage Driven by Genomic Dynamics. Xu, Jiaxin,Wang, Yu,Zhou, Haibo,Li, Mingen,Wang, Yang,Wang, Lingwei,Mei, Hui,Dai, Junbiao,Chen, Shanze,Huang, Xiaoluo. 2026

[2]Prospects of Blockchain Technology in China's Industrial Hemp Industry. Liu, Haolu,Zhang, Bin,Huang, Jicheng,Tian, Kunpeng,Shen, Cheng. 2023

[3]A Traceability System of Livestock Products Based on Blockchain and the Internet of Things. Yuejing Chen,Ailian Zhou,Xiaohe Liang,Nengfu Xie,Huijuan Wang,Xiaoyu Li. 2021

[4]Food cold chain management improvement: A conjoint analysis on COVID-19 and food cold chain systems. Jianping Qian,Qiangyi Yu,Li Jiang,Han Yang,Wenbin Wu. 2022

[5]Speeding at the Edge: An Efficient and Secure Redactable Blockchain for IoT-Based Smart Grid Systems. Youshui Lu,Xiaojun Tang,Lei Liu,F. Richard Yu,Schahram Dustdar. 2023

[6]Integrating AI with detection methods, IoT, and blockchain to achieve food authenticity and traceability from farm-to-table. Zhaolong Liu,Xinlei Yu,Nan Liu,Cuiling Liu,Ao Jiang,Lanzhen Chen. 2025

[7]Lightweight Fruit-Detection Algorithm for Edge Computing Applications. Wenli Zhang,Yuxin Liu,Kaizhen Chen,Huibin Li,Yulin Duan,Wenbin Wu,Yun Shi,Wei Guo. 2021

[8]A lightweight tea bud detection model based on Yolov5. Gui, Zhiyong,Chen, Jianneng,Li, Yang,Chen, Zhiwei,Wu, Chuanyu,Dong, Chunwang. 2023

[9]A Non-Destructive Method for Identification of Tea Plant Cultivars Based on Deep Learning. Yi Ding,Haitao Huang,Hongchun Cui,Xinchao Wang,Yun Zhao. 2023

[10]Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory. Xinfa Wang,Zhenwei Wu,Meng Jia,Tao Xu,Canlin Pan,Xuebin Qi,Mingfu Zhao. 2023

[11]VGNet: A Lightweight Intelligent Learning Method for Corn Diseases Recognition. Xiangpeng Fan,Zhibin Guan. 2023

[12]Small target tea bud detection based on improved YOLOv5 in complex background. Mengjie Wang,Yang Li,Hewei Meng,Zhiwei Chen,Zhiyong Gui,Yaping Li,Chunwang Dong. 2024

[13]Lightweight cotton diseases real-time detection model for resource-constrained devices in natural environments. Pan Pan,Mingyue Shao,Peitong He,Lin Hu,Sijian Zhao,Longyu Huang,Guomin Zhou,Jianhua Zhang. 2024

[14]Weed Recognition at Soybean Seedling Stage Based on YOLOV8nGP + NExG Algorithm. Tao Sun,Longfei Cui,Lixuan Zong,Songchao Zhang,Yuxuan Jiao,Xinyu Xue,Yongkui Jin. 2024

[15]Estimation of the orientation of potatoes and detection bud eye position using potato orientation detection you only look once with fast and accurate features for the movement strategy of intelligent cutting robots. Jie Huang,Xiangyou Wang,Chengqian Jin,Fernando Auat Cheein,Xinyu Yang. 2025

[16]Design and Research on a Reed Field Obstacle Detection and Safety Warning System Based on Improved YOLOv8n. Zhang, Yuanyuan,Mu, Zhongqiu,Tian, Kunpeng,Zhang, Bing,Huang, Jicheng. 2025

[17]YOLO-YSTs: An Improved YOLOv10n-Based Method for Real-Time Field Pest Detection. Yiqi Huang,Zhenhao Liu,Hehua Zhao,Chao Tang,Bo Liu,Zaiyuan Li,Fanghao Wan,Wanqiang Qian,Xi Qiao. 2025

[18]Reb-DINO: A Lightweight Pedestrian Detection Model With Structural Re-Parameterization in Apple Orchard. Li, Ruiyang,Song, Ge,Wang, Shansong,Zeng, Qingtian,Yuan, Guiyuan,Ni, Weijian,Xie, Nengfu,Xiao, Fengjin. 2025

[19]YOLOv8-MSP-PD: A Lightweight YOLOv8-Based Detection Method for Jinxiu Malus Fruit in Field Conditions. Yi Liu,Xiang Han,Hongjian Zhang,Shuangxi Liu,Wei Ma,Yinfa Yan,Linlin Sun,Linlong Jing,Yongxian Wang,Jinxing Wang. 2025

[20]Soybean–Corn Seedling Crop Row Detection for Agricultural Autonomous Navigation Based on GD-YOLOv10n-Seg. Tao Sun,Feixiang Le,Chen Cai,Yongkui Jin,Xinyu Xue,Longfei Cui. 2025

作者其他论文 更多>>