Camera-Recognizable and Human-Invisible Labelling for Privacy Protection

Modern mobile devices, especially smartphones, are widely equipped with cameras, which enable their owners to capture every memorable moment or scenery, such as parties with friends. However, significant privacy concerns are posed by the potential possibility of revealing a large amount of privacy contained by photos, e.g., portrait of a person. World Driven Access Control (WDAC) [1], which triggered by environment signs rather than user operations, provides a privacy access control mechanism for photographed objects (including people and other objects containing sensitive information). WDAC supports several policy label forms which either have impact on the normal appearance of objects or rely on sensors other than camera to sense policy labels. This paper proposes an approach of labelling with a Near Infrared (NIR) label which relies only on camera and has no influence on normal appearance of objects. When an object wears a NIR label, surrounding people are unaware of the existence of the labels. Meanwhile, we design and implement a policy label recognition and policy enforcement system based on Android. The system is able to recognize NIR labels binding to objects, and then enforce privacy policies, such as Gaussian Blur, on these objects to protect their privacy.