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Title |
Multi-Determiner Protection of Private Data in Pervasive Computing Environments |
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Author |
Anis Yousefi, Rasool Jalili, Mahdi Niamanesh |
| Citation |
Vol. 6 No. 12 pp. 239-248 |
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Abstract |
Protection of private data is one of the most challenging issues threatening the success of Pervasive Computing (PC). Regarding the principles of privacy and the vision of pervasive computing, one of the most troublesome problems is how to provide people's control of their data while not distract them to a great extent. A suitable approach for protecting people's private data in PC environments should consider the intention of all influential entities (data determiners), and invisibly gain their consent by applying their desired preferences. In extension of the current approaches which consider a single set of preference rules for a private data item when deciding about its disclosure, we propose dealing with different preferences of all involved determiners in a distributed manner. In this paper we investigate possible determiners of private data and propose a set of required meta-data as well as a multi-determiner protection procedure to protect private data with regard to the preferences of its determiners. Moreover, we propose the DELEGATION behavior as a determiner's response to a request instead of ACCEPT or REJECT. We demonstrate the efficiency of the suggested procedure and present a prototype implementation of a multi-determiner architecture to realize the protection procedure. |
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Keywords |
Data Privacy, Pervasive Computing, Multi-Determiner Private Data. |
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