Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 37, Pages: 1-6
K. R. Jansi1 * and S. V. Kasmir Raja2
1 Department of Computer Science and Engineering, SRM University, Kattankulathur, Chennai - 603203, Tamil Nadu, India; [email protected]
2 SRM University, Kattankulathur, Chennai - 603203, Tamil Nadu, India; [email protected]
*Author for correspondence
Department of Computer Science and Engineering
Email: [email protected]
Mobile devices play a vital role in our day to day life. The various sensing modalities available in mobile devices are identified and justify the growth of the capabilities on today’s smart phones.Taking advantage of the sensing capabilities of the mobile devices paves way for a new era of network, referred as people centric sensing network. In this paper, a broad study about the applications, architectural components and the existing privacy and security architectures available are discussed. The applications of mobile sensing are categorized as personal, social and public sensing based on what they sense, how they share and infer. All these applications clearly depict the roles played by people. People may act as end users, as participants and as application administrators. Since people are in the loop, the basic privacy and security requirements are analyzed that can be realized as the need in the design of any mobile phone sensing systems. The possible threats that arise in this sensing context may be due to both internal and external entities. The strategies and types of adversarial models in the people centric sensing approach provides us light to how the framework works and solutions needed. Existing literature in terms of privacy preserving data aggregation schemes and security Frameworks are also discussed in detail. Applications: The model clearly portraits the importance of people who are no more only passive data users. More focus has to be given on privacy preserving models to make the system more acceptable by the people.
Keywords: Design, Mobile Sensing Systems, Participatory Sensing, People Centric Sensing, Privacy, System Model
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