earticle

논문검색

Sensitive-resisting Relation Social Network Privacy Protection Model

원문정보

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

저자정보

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

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.