DocumentCode :
1801495
Title :
A Privacy Framework for Personal Self-Improving Smart Spaces
Author :
Liampotis, N. ; Roussaki, I. ; Papadopoulou, E. ; Abu-Shaaban, Y. ; Williams, M.H. ; Taylor, N.K. ; McBurney, S.M. ; Dolinar, K.
Author_Institution :
Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Athens, Greece
Volume :
3
fYear :
2009
fDate :
29-31 Aug. 2009
Firstpage :
444
Lastpage :
449
Abstract :
There are various critical privacy issues that need to be addressed in the majority of smart space environments. This paper elaborates on the design of a privacy protection framework for personal self-improving smart spaces (PSSs), a concept introduced by the persist project consortium. Compared to other smart spaces, such as smart homes and vehicles, this new paradigm provides a truly ubiquitous and fully personalizable user centric environment. However, the information that needs to be collected, processed and distributed in such an environment is by nature highly privacy sensitive, as it includes user profile data and preferences, as well as data regarding the past, current and even future user activities and context in general. In this respect, the designed privacy framework aims to address all privacy issues that arise by providing facilities which support multiple digital identities of PSS owners and privacy preferences for deriving privacy policies based on the context and the trustworthiness of the third parties that interact with PSSs.
Keywords :
data privacy; security of data; PSS owner; activity data; multiple digital identity; persist project consortium; personal self-improving smart space; personalizable user centric environment; privacy policy derivation; privacy protection framework; privacy sensitive nature; smart space environment; user preference; user profile data; Computer security; Identity management systems; Intelligent vehicles; National security; Pervasive computing; Privacy; Protection; Smart homes; Space technology; Space vehicles; digital identity management; personal smart space; privacy; privacy policy negotiation; privacy preferences; trust evaluation; trust inference;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Engineering, 2009. CSE '09. International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-5334-4
Electronic_ISBN :
978-0-7695-3823-5
Type :
conf
DOI :
10.1109/CSE.2009.148
Filename :
5283193
Link To Document :
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