English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 95844/126434 (76%)
Visitors : 31567995      Online Users : 465
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 理學院 > 資訊科學系 > 會議論文 >  Item 140.119/74630
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/74630

    Title: Anonymization for multiple released social network graphs
    Authors: Wang, C.-J.L.;Wang, E.T.;Chen, Arbee L P
    Contributors: 資科系
    Keywords: Anonymization;Data utilities;Effect of time;Privacy preservation;Privacy preserving;Query answering;Real data sets;Time-serial data;Data mining;Data privacy;Graphic methods;Time series analysis;Social networking (online)
    Date: 2013
    Issue Date: 2015-04-16 17:30:33 (UTC+8)
    Abstract: Recently, people share their information via social platforms such as Facebook and Twitter in their daily life. Social networks on the Internet can be regarded as a microcosm of the real world and worth being analyzed. Since the data in social networks can be private and sensitive, privacy preservation in social networks has been a focused study. Previous works develop anonymization methods for a single social network represented by a single graph, which are not enough for the analysis on the evolution of the social network. In this paper, we study the privacy preserving problem considering the evolution of a social network. A time-series of social network graphs representing the evolution of the corresponding social network are anonymized to a sequence of sanitized graphs to be released for further analysis. We point out that naively applying the existing approaches to each time-series graph will break the privacy purposes, and propose an effective anonymization method extended from an existing approach, which takes into account the effect of time for releasing multiple anonymized graphs at one time. We use two real datasets to test our method and the experiment results demonstrate that our method is very effective in terms of data utility for query answering. © Springer-Verlag 2013.
    Relation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),Volume 7819 LNAI(2), Pages 99-110,17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013; Gold Coast, QLD; Australia; 14 April 2013 到 17 April 2013; 代碼 102450
    Data Type: conference
    Appears in Collections:[資訊科學系] 會議論文

    Files in This Item:

    File Description SizeFormat

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback