Biblio

The recent emergence of smartphones, cloud computing, and the Internet of Things has brought about the explosion of data creation. By collating and merging these enormous data with other information, services that use information become more sophisticated and advanced. However, at the same time, the consideration of privacy violations caused by such merging is indispensable. Various anonymization methods have been proposed to preserve privacy. The conventional perturbation-based anonymization method of location data adds comparatively larger noise, and the larger noise makes it difficult to utilize the data effectively for secondary use. In this research, to solve these problems, we first clarified the definition of privacy preservation and then propose TMk-anonymity according to the definition.

Wireless sensor networks (WSNs) are implemented in various Internet-of-Things applications such as energy management systems. As the applications may involve personal information, they must be protected from attackers attempting to read information or control network devices. Research on WSN security is essential to protect WSNs from attacks. Studies in such research domains propose solutions against the attacks. However, they focus mainly on the security measures rather than on their ease in implementation in WSNs. In this paper, we propose a coordination middleware that provides an environment for constructing updatable WSNs for security. The middleware is based on LINC, a rule-based coordination middleware. The proposed approach allows the development of WSNs and attaches or detaches security modules when required. We implemented three security modules on LINC and on a real network, as case studies. Moreover, we evaluated the implementation costs while comparing the case studies.