RETRACTED: Machine Learning-Based Holistic Privacy Decentralized Framework for Big Data Security and Privacy in Smart City (Retracted Article)

被引：7

作者：

Zhang, Yi Jie ^{[1
]}

Alazab, Mamoun ^{[2
]}

Muthu, BalaAnand ^{[3
]}

机构：

[1] Shan Xi Univ, Business Coll, Taiyuan 030031, Shanxi, Peoples R China

[2] Charles Darwin Univ, IT & Environm, Darwin, NT, Australia

[3] Adhiyamaan Coll Engn, Dept Comp Sci & Engn, Hosur, India

来源：

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING | 2023年 / 48卷 / 03期

关键词：

Machine learning; Big data; Security; Privacy; Smart city; CITIES; CHALLENGES; MANAGEMENT; BLOCKCHAIN;

D O I：

10.1007/s13369-021-06028-1

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Big data growth and the evolution of IoT technology figured prominently in making smart city projects feasible. The risk factors for big data in the smart city include data security, and privacy is considered an important factor. In this paper, machine learning-based holistic privacy decentralized framework (ML-HPDF) has been proposed to enhance public safety and confidentiality of the data accessibility for a statistics consumer. Hence, double authentication private-preserving analysis is integrated with ML-HPDF to guarantee the accessibility of transaction data, data providers' secrecy, and fairness between information providers and information customers. The simulation investigation is undertaken based on safety, efficiency, and confidentiality.

引用

页码：4141 / 4141

页数：1

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