LooM: An Anonymity Quantification Method in Pervasive Computing Environments

We propose a novel anonymity quantification method for privacy protection in pervasive computing environments. Its main feature is that it can quantitatively control anonymity by a single value (disclosure threshold value) using a classification algorithm of the decision tree. The value is not affected by the user set size or the contents of private information. This property was confirmed by evaluation using sample databases. In order to decide the disclosure threshold value for controlling anonymity, we established a model of privacy information disclosure that achieves a balance (equilibrium point) between users´ privacy protection requirements and service providers´ disclosure requirements. Applying Web questionnaire data to this model we found the equilibrium point for each service