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Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System

文献类型：期刊论文

作者Yao, Zhengyi5; Tan, Liang3,4,5; Yi, Junhao2; Fu, Luxia5; Zhang, Zhuang5; Tan, Xinghong5; Xie, Jingxue5; She, Kun1; Yang, Peng5; Wu, Wanjing5
刊名SYMMETRY-BASEL
出版日期2024
卷号16期号:1页码:29
关键词data privacy location privacy smart logistics platform privacy protection
DOI10.3390/sym16010068
英文摘要An intelligent logistics system is a production system based on the Internet of Things (IoT), and the logistics information of humans has a high degree of privacy. However, the current intelligent logistics system only protects the privacy of shippers and consignees, without any privacy protection for carriers, which will not only cause carriers' privacy leakage but also indirectly or directly affect the logistics efficiency. It is particularly worth noting that solving this problem requires one to consider the balance between privacy protection and operational visibility. So, the local privacy protection algorithm epsilon-L_LDP for carriers' multidimensional numerical sensitive data and epsilon-LT_LDP for carrier location sensitive data are proposed. For epsilon-L_LDP, firstly, a personalized and locally differentiated privacy budgeting approach is used. Then, the multidimensional data personalization perturbation mechanism algorithm L-PM is designed. Finally, the multidimensional data are perturbed using L-PM. For epsilon-LT_LDP, firstly, the location area is matrix-partitioned and quadtree indexed, and the location data are indexed according to the quadtree to obtain the geographic location code in which it is located. Secondly, the personalized random response perturbation algorithm L-RR for location trajectory data is also designed. Finally, the L-RR algorithm is used to implement the perturbation of geolocation-encoded data. Experiments are conducted using real and simulated datasets, the results show that the epsilon-L_LDP algorithm and epsilon-LT_LDP algorithm can better protect the privacy information of carriers and ensure the availability of carrier data during the logistics process. This effectively meets the balance between the privacy protection and operational visibility of the intelligent logistics system.
资助项目National Natural Science Foundation of China
WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:001151335000001
出版者MDPI
源URL[http://119.78.100.204/handle/2XEOYT63/38393]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Tan, Liang
作者单位1.Univ Elect Sci & Technol China, Coll Informat & Software Engn, Chengdu 610054, Peoples R China
2.Chengdu Jincheng Coll, Software Engn Dept, Chengdu 611731, Peoples R China
3.Univ Elect Sci & Technol China, Inst Cyberspace Secur, Chengdu 610054, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing 100864, Peoples R China
5.Sichuan Normal Univ, Coll Comp Sci, Chengdu 610066, Peoples R China
推荐引用方式
GB/T 7714		 Yao, Zhengyi,Tan, Liang,Yi, Junhao,et al. Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System[J]. SYMMETRY-BASEL,2024,16(1):29.
APA Yao, Zhengyi.,Tan, Liang.,Yi, Junhao.,Fu, Luxia.,Zhang, Zhuang.,...&Yu, Ziyuan.(2024).Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System.SYMMETRY-BASEL,16(1),29.
MLA Yao, Zhengyi,et al."Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System".SYMMETRY-BASEL 16.1(2024):29.

入库方式： OAI收割

来源：计算技术研究所

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