ARTSense: Anonymous reputation and trust in participatory sensing

Xinlei Wang, Wei Cheng, Prasant Mohapatra, Tarek Abdelzaher

Research output: Chapter in Book/Report/Conference proceedingConference contribution


With the proliferation of sensor-embedded mobile computing devices, participatory sensing is becoming popular to collect information from and outsource tasks to participating users. These applications deal with a lot of personal information, e.g., users' identities and locations at a specific time. Therefore, we need to pay a deeper attention to privacy and anonymity. However, from a data consumer's point of view, we want to know the source of the sensing data, i.e., the identity of the sender, in order to evaluate how much the data can be trusted. 'Anonymity' and 'trust' are two conflicting objectives in participatory sensing networks, and there are no existing research efforts which investigated the possibility of achieving both of them at the same time. In this paper, we propose ARTSense, a framework to solve the problem of 'trust without identity' in participatory sensing networks. Our solution consists of a privacy-preserving provenance model, a data trust assessment scheme and an anonymous reputation management protocol. We have shown that ARTSense achieves the anonymity and security requirements. Validations are done to show that we can capture the trust of information and reputation of participants accurately.

Original languageEnglish (US)
Title of host publication2013 Proceedings IEEE INFOCOM 2013
Number of pages9
StatePublished - 2013
Event32nd IEEE Conference on Computer Communications, IEEE INFOCOM 2013 - Turin, Italy
Duration: Apr 14 2013Apr 19 2013

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Other32nd IEEE Conference on Computer Communications, IEEE INFOCOM 2013

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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