Earticle

초록

영어

The existing social network privacy protection method mostly aims at the individuals of the social network, which cannot protect effectively the sensitive relations in the social network. Therefore, this paper proposes a new personalized K_L model. This model requires each sensitive relation with the sensitive relational point have l at least, and also the point with the same requirement has k at least. Thus, the attack has been resisted during the protection of the sensitive relations. Through seeking the most figure of merit sequence and considering individual sensitive attribute, the L-diversity method is applied so as to guarantee the least side and reduce the anonymous cost. Through the data set experiment, this paper proposes new personalized model K_L, which has the high anonymous quality and can effectively protect user's privacy in the social network.

목차

Abstract
 1. Introduction
 2. Personalization K_L Model
  2.1 Basic Concepts
 3. Implementation of Personalized K_L Model
  3.1 l-diversity Anonymity
  3.2 K -degree Anonymity
 4. Anonymous Posting Algorithm
 5. The Experimental Results and Analysis
  5.1 Experimental Environment
  5.2 Experimental Instructions
 6. Conclusion
 References

키워드

저자

• Han Yan [ Engineering Training Center, Inner Mongolia University of Science &Technology, Baotou, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605