The data modeling considered correlation of information leakage detection and privacy violation
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Loose tweets: an analysis of privacy leaks on twitter
Proceedings of the 10th annual ACM workshop on Privacy in the electronic society
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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.