Entropy Based Personal Privacy Measurement in Ubiquitous Computing

Abstract

This paper designs a scheme, which can quantize the personal privacy based on profile and context, using entropy. It aims to configure the person's privacy in numerical form that can be dynamically adjusted instead of using the traditional simple rule engine. In addition, we design the scenario to design a adjust algorithm to modify the privacy based on numerical values.