A Lightweight Pseudonymization Approach for Textual Personal Information

Sharing personal information benefits both users and third parties in many ways such as recommendation systems, user modeling, etc. Recent advances in sensor networks and personal archives enable us to record all of our digital objects such as emails, social networking activities and life events (life logging). These information objects are privacy sensitive and here we introduce a lightweight pseudonymization framework which enables users to benefit from sharing their personal information while considering their privacy. This framework enables users with fewer IT skills to pseudonymize their text based information. Tools which improve users privacy, are going to be necessary in the near future. This is due to the fact that on one hand these tools enable information owners to share their information, while being aware of what they are sharing, and thus the third party access is more transparent than before. On the other hand new personal information objects, which are valuable for third parties, are going to be more privacy sensitive than before such as biological information. Author Keywords

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