Abstract:
Mobile devices are changing the way that people conduct their daily businesses and carry out their works. More and more people are using mobile devices to view personal or work-related information in public places, e.g. café, train, etc. This type of information might contain sensitive data, e.g. personal information, trade secrets, etc. As high-resolution cameras are widely used and public places are always crowded, viewing information in public carries the risk of having the screen filmed by cameras or being peeked by the near-by people. This paper proposes a privacy guard service to help people to safe-guard their sensitive data while viewing information in public. The service uses machine learning and natural language processing techniques to identify sensitive information in documents. The service automatically converts the sensitive information to meaningless strings. Text-to-speech code is embedded behind the symbols. The code enable the users to listen to the content of the original sensitive information by using an earphone when the users tap on the symbols. As a result, users are able to view their sensitive data in public without worrying about privacy leaks due to visual observation attacks.
