Architecture for adaptable smart spaces oriented on user privacy

Adam Wójtowicz , Daniel Wilusz


Smart spaces are populated by users having evolving preferences that, directly or indirectly, reflect their spatial, temporal, financial and interaction patterns of service usage. These data, if disclosed, could draw a detailed picture of users’ life in public spaces. Protection of privacy-sensitive data is especially significant in scenarios employing negotiations where many non-trusted service providers, service consumers and payment processes are involved. For such scenarios an architecture and a protocol for secure and privacy-preserving smart space usage have been developed. The presented approach relies on a trusted party operating as a public service in the ‘security infrastructure as a service’ model. The solution is designed to minimize the risk of users privacy violation from the side of service providers and attackers impersonating regular users, as well as the risk of violating privacy of users’ payment patterns from the side of payment authorities. All parties benefit from fast and secure micropayments allowing for pay-per-use model implementation, which fulfils the non-invasiveness requirement of ubiquitous services. The presented use case scenario illustrates the possible application of this approach, and adversary model explains its privacy attributes.
Author Adam Wójtowicz (WIiGE / KTI)
Adam Wójtowicz,,
- Department of Information Technology
, Daniel Wilusz (WIiGE / KTI)
Daniel Wilusz,,
- Department of Information Technology
Journal seriesLogic Journal of the IGPL, ISSN 1367-0751, e-ISSN 1368-9894, (A 30 pkt)
Issue year2017
Publication size in sheets0.7
Keywords in Englishuser privacy, privacy-preserving systems, security protocol, smart spaces, smart environments, ubiquitous computing
ASJC Classification1211 Philosophy
Languageen angielski
Score (nominal)30
Score sourcejournalList
ScoreMinisterial score = 30.0, 27-04-2020, ArticleFromJournal
Publication indicators WoS Citations = 1; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 0.907; WoS Impact Factor: 2017 = 0.449 (2) - 2017=0.446 (5)
Citation count*3 (2020-11-24)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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