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
Link To Document :
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