“ When wireless is perfectly applied the whole earth will be converted into a huge brain, which in fact it is, all things being particles of a real and rhythmic whole. We shall be able to communicate with one another instantly, irrespective of distance. Not only this, but through television and telephony we shall see and hear one another as perfectly as though we were face to face, despite intervening distances of thousands of miles; and the instruments through which we shall be able to do his will be amazingly simple compared with our present telephone. A man will be able to carry one in his vest pocket.
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~Nikola Tesla 1926~

Research Project

Large volumes of personal information are being disclosed in online social networks and made available to huge numbers of potential audiences; thus, posing great risk to users privacy, consequently nearly all online social networks have introduced privacy settings (with varying degrees of granularity)that allows users to regulate their personal information disclosure; however, the complex and time consuming nature of these settings, causes many users not to configure their settings and continue using the online social networks' services with the default settings configurations, which are too permissive. my research focus on building a recommender system that makes use of the knowledge and expertise of existing members of the social network, to make accurate privacy settings recommendations, eliminating the overhead of configuring privacy settings, and at the same time insuring a relatively privacy preserving social networking experience, our system utilises machine learning and data mining techniques to perform the recommendations.