Table of Content

Open Access

ARTICLE

Research on Protecting Information Security Based on the Method of Hierarchical Classification in the Era of Big Data

Guangyong Yang1,*, Mengke Yang2,*, Shafaq Salam3, Jianqiu Zeng4
School of Economics & Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
School of Automation, Beijing University of Posts and Telecommunications, Beijing , 100876, China.
Beaconhouse School System, Peshawar, Pakistan .
School of Economics & Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
*Corresponding Authors: Yang Guangyong. Email: .

Journal of Cyber Security 2019, 1(1), 19-28. https://doi.org/10.32604/jcs.2019.05947

Abstract

Big data is becoming increasingly important because of the enormous information generation and storage in recent years. It has become a challenge to the data mining technique and management. Based on the characteristics of geometric explosion of information in the era of big data, this paper studies the possible approaches to balance the maximum value and privacy of information, and disposes the Nine-Cells information matrix, hierarchical classification. Furthermore, the paper uses the rough sets theory to proceed from the two dimensions of value and privacy, establishes information classification method, puts forward the countermeasures for information security. Taking spam messages for example, the massive spam messages can be classified, and then targeted hierarchical management strategy was put forward. This paper proposes personal Information index system, Information management platform and possible solutions to protect information security and utilize information value in the age of big data.

Keywords

Big data, hierarchical classification, rough sets, information index system

Cite This Article

G. Yang, M. Yang, S. Salam and J. Zeng, "Research on protecting information security based on the method of hierarchical classification in the era of big data," Journal of Cyber Security, vol. 1, no.1, pp. 19–28, 2019.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1906

    View

  • 1590

    Download

  • 0

    Like

Share Link

WeChat scan