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IncogniSense: An anonymity-preserving reputation frameworkfor participatory sensing applications
Tech Univ Darmstadt, Secure Mobile Networking Lab, Darmstadt, Germany.
Tech Univ Darmstadt, Secure Mobile Networking Lab, Darmstadt, Germany.
Tech Univ Darmstadt, Secure Mobile Networking Lab, Darmstadt, Germany.
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap. (Privacy and Security Group)
Vise andre og tillknytning
2012 (engelsk)Inngår i: Proceedings of the 10th Annual IEEE In-ternational Conference on Pervasive Computing and Communications (PerCom2012) / [ed] Silvia Giordano, Marc Langheinrich, and Albrecht Schmidt, IEEE, 2012, s. 135-143Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Reputation systems rate the contributions to participatory sensing campaigns from each user by associatinga reputation score. The reputation scores are used to weedout incorrect sensor readings. However, an adversary can de-anonmyize the users even when they use pseudonyms by linking the reputation scores associated with multiple contributions. Since the contributed readings are usually annotated with spatio-temporal information, this poses a serious breach of privacy for the users. In this paper, we address this privacy threat by proposing a framework called IncogniSense. Our system utilizes periodic pseudonyms generated using blind signature and relies on reputation transfer between these pseudonyms. The reputation transfer process has an inherent trade-off between anonymity protection and loss in reputation. We investigate by means of extensive simulations several reputation cloaking schemes that address this tradeoff differently. Our system is robust against reputation corruption and a proof-of-concept implementation demonstrates that the associated overheads are minimal.

sted, utgiver, år, opplag, sider
IEEE, 2012. s. 135-143
Serie
International Conference on Pervasive Computing and Communications, ISSN 2474-2503
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-27803DOI: 10.1109/PerCom.2012.6199860ISI: 000309103700019ISBN: 978-1-4673-0256-2 (tryckt)OAI: oai:DiVA.org:kau-27803DiVA, id: diva2:628240
Konferanse
10th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2012)
Tilgjengelig fra: 2013-06-13 Laget: 2013-06-13 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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