• DocumentCode
    2394384
  • Title

    Data Leak Prevention through Named Entity Recognition

  • Author

    Gómez-Hidalgo, José María ; Martín-Abreu, José Miguel ; Nieves, Javier ; Santos, Igor ; Brezo, Felix ; Bringas, Pablo G.

  • Author_Institution
    Optenet, Madrid, Spain
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Firstpage
    1129
  • Lastpage
    1134
  • Abstract
    The rise of the social web has brought a series of privacy concerns and threats. In particular, data leakage is a risk that affects the privacy of not only companies but individuals. Although there are tools that can prevent data losses, they require a prior step that involves the sensitive data to be properly identified. In this paper, we propose a new automatic approach that applies Named Entity Recognition (NER) to prevent data leaks. We conduct an empirical study with real-world data and show that this NER-based approach can enhance the prevention of data losses. In addition, we present and detail the implementation of a prototype built with these techniques and show how it can be used by both particulars and companies in order to handle data losses.
  • Keywords
    information retrieval; security of data; social networking (online); data leak prevention; named entity recognition; social Web; Accuracy; Companies; Prototypes; Security; Training; Twitter; computer security; data leak prevention; named entity recognition; natural language processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Computing (SocialCom), 2010 IEEE Second International Conference on
  • Conference_Location
    Minneapolis, MN
  • Print_ISBN
    978-1-4244-8439-3
  • Electronic_ISBN
    978-0-7695-4211-9
  • Type

    conf

  • DOI
    10.1109/SocialCom.2010.167
  • Filename
    5590530