English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113311/144292 (79%)
Visitors : 50933344      Online Users : 997
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
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 >  Item 140.119/74630


    Please use this identifier to cite or link to this item: https://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
    10.1007/978-3-642-37456-2_9
    Data Type: conference
    Appears in Collections:[資訊科學系] 會議論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML21002View/Open


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


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback