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Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 10
3077-3082

Sensitive attribute recognition and classification algorithm for structure dataset

He Wenzhu1a,1b
Peng Changgen1a,1b
Wang Maoni1a,1b
Ding Xing1a,1b
Fan Meimei1c
Ding Hongfa2
1. a. College of Computer Science & Technology, b. State key Laboratory of Public Big Data, c. College of Mathematics & Statistics, Guizhou University, Guiyang 550025, China
2. College of Information, Guizhou University of Finance & Economics, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2019.05.0187

Abstract

How to automatically identify and classify sensitive attributes(fields) of structured datasets, which are confused by code in the production environment, has become a bottleneck for structured data privacy protection. This paper proposed an automatic recognition and classification algorithm of sensitive attributes. This algorithm introduced information entropy to define the sensitivity of the attribute, identified and quantified sensitivity of the sensitive attributes by sensitivity clustering of attri-butes and association rules mining among attributes. Further, by analyzing the mutual information correlations and association rules among grouped the sensitive attribute clusters, the sensitive attributes and quantified the average sensitive metrics of these groups. Thus, this algorithm achieved the classifying of the sensitive attributes. Experiments show that the algorithm can identify the sensitive attributes of any structured dataset and classify the sensitive attributes, with higher efficiency and accuracy. Comparison shows that this algorithm can achieve both recognition and classification of sensitive attributes. It's not necessary to know the characteristics of attributes and sensitive feature dictionary. Both of the correlation and association among attributes are took into account by this algorithm.

Foundation Support

国家自然科学基金资助项目(U1836205,61662009,61772008,11761020)
贵州省科技计划项目(黔科合重大专项字[2018]3001,黔科合重大专项字[2018]3007,黔科合重大专项字[2017]3002,黔科合支撑[2019]2004,黔科合支撑[2018]2162,黔科合基础[2019]1049,黔科合基础[2017]1045)
贵州财经大学科研基金资助项目(2017XJC01)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.05.0187
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 10
Section: Technology of Information Security
Pages: 3077-3082
Serial Number: 1001-3695(2020)10-040-3077-06

Publish History

[2020-10-05] Printed Article

Cite This Article

何文竹, 彭长根, 王毛妮, 等. 面向结构化数据集的敏感属性识别与分级算法 [J]. 计算机应用研究, 2020, 37 (10): 3077-3082. (He Wenzhu, Peng Changgen, Wang Maoni, et al. Sensitive attribute recognition and classification algorithm for structure dataset [J]. Application Research of Computers, 2020, 37 (10): 3077-3082. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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