Privacy Protection by Anonymizing Based on Status of Provider and Community

When a user receives personal services from a service provider, the service can be of a higher quality if the user pro-vides more personal information. However, the risk of privacy violation could increase. Therefore, this paper proposes a privacy protection method that realizes avoidance of unwanted informa-tion disclosure by controlling disclosable attributes according to the results from monitoring two elements: user background in-formation of the provider and user community status. This is done before disclosing individual attributes corresponding to the privacy policy (i.e., the required anonymity level) by each user. The system architecture based on the aforementioned is also pro-posed. The validity of the proposed methods was confirmed by a desk model

Protecting users’ anonymity in pervasive computing environments

The large scale adoption of adaptive services in pervasive and mobile computing is likely to be conditioned to the availability of reliable privacy-preserving technologies. Unfortunately, the research in this field can still be considered in its infancy. This paper considers a specific pervasive computing scenario, and shows that the application of state-of-the-art techniques for the anonymization of service requests is insufficient to protect the privacy of users. A specific class of attacks, called shadow attacks, is formally defined and a set of defense techniques is proposed. These techniques are validated through the use of a simulator and an extensive set of experiments