Data supervision and security in large data repositories

Ensuring data security in large data repositories is a challenging task as the volume and the nature of the data to secure constantly evolves. Large repositories are mostly composed of documents expressed in natural language and as a result they are a rich source of information. Given the importance of personal data protection, this proposal explores new methods to mine networks of communications between users and detect improper dissemination of sensitive information. Our objectives are i) to develop algorithms to automatically identify sensitive information from a document content; ii) understand how information is exchanged in an organization by exploiting communication links between users, and iii) develop automated approaches to prevent undesired dissemination of information.

Faculty Supervisor:

Marie-Jean Meurs


Antoine Briand


Netmail Inc


Computer science


Information and communications technologies




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