An integrated reward and reputation mechanism for MCS preserving users’ privacy

Cristian Tanas; Sergi Delgado-Segura; Jordi Herrera-Joancomartí

doi:10.1007/978-3-319-29883-2_6

An integrated reward and reputation mechanism for MCS preserving users’ privacy

Cristian Tanas, Sergi Delgado-Segura, Jordi Herrera-Joancomartí^*

^*Corresponding author for this work

Dept. d’Enginyeria de la Informació i les Comunicacions

Research output: Contribution to journal › Article › Research › peer-review

13 Citations (Scopus)

Abstract

Mobile Crowd Sensing (MCS) presents numerous and unique research challenges most of them based on the fact that human participation is in the loop. In this paper we analyse three of the most important: user participation, data sensing quality and user anonymity. To solve them, we present PaySense, a general framework for user rewarding and reputation accountability that preserves users’ privacy using cryptocurrencies. Furthermore, we detailed an implementable system using bitcoins.

Original language	American English
Pages (from-to)	83-99
Number of pages	17
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOIs	https://doi.org/10.1007/978-3-319-29883-2_6
Publication status	Published - 2016

Access to Document

10.1007/978-3-319-29883-2_6

Cite this

@article{07c62755ed1c4d46a8d50c26241c4d7b,

title = "An integrated reward and reputation mechanism for MCS preserving users{\textquoteright} privacy",

abstract = "Mobile Crowd Sensing (MCS) presents numerous and unique research challenges most of them based on the fact that human participation is in the loop. In this paper we analyse three of the most important: user participation, data sensing quality and user anonymity. To solve them, we present PaySense, a general framework for user rewarding and reputation accountability that preserves users{\textquoteright} privacy using cryptocurrencies. Furthermore, we detailed an implementable system using bitcoins.",

author = "Cristian Tanas and Sergi Delgado-Segura and Jordi Herrera-Joancomart{\'i}",

year = "2016",

doi = "10.1007/978-3-319-29883-2_6",

language = "Ingl{\'e}s estadounidense",

pages = "83--99",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

}

An integrated reward and reputation mechanism for MCS preserving users’ privacy. / Tanas, Cristian; Delgado-Segura, Sergi; Herrera-Joancomartí, Jordi.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, p. 83-99.

Research output: Contribution to journal › Article › Research › peer-review

TY - JOUR

T1 - An integrated reward and reputation mechanism for MCS preserving users’ privacy

AU - Tanas, Cristian

AU - Delgado-Segura, Sergi

AU - Herrera-Joancomartí, Jordi

PY - 2016

Y1 - 2016

N2 - Mobile Crowd Sensing (MCS) presents numerous and unique research challenges most of them based on the fact that human participation is in the loop. In this paper we analyse three of the most important: user participation, data sensing quality and user anonymity. To solve them, we present PaySense, a general framework for user rewarding and reputation accountability that preserves users’ privacy using cryptocurrencies. Furthermore, we detailed an implementable system using bitcoins.

AB - Mobile Crowd Sensing (MCS) presents numerous and unique research challenges most of them based on the fact that human participation is in the loop. In this paper we analyse three of the most important: user participation, data sensing quality and user anonymity. To solve them, we present PaySense, a general framework for user rewarding and reputation accountability that preserves users’ privacy using cryptocurrencies. Furthermore, we detailed an implementable system using bitcoins.

UR - http://www.scopus.com/inward/record.url?scp=84961133233&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-29883-2_6

DO - 10.1007/978-3-319-29883-2_6

M3 - Artículo

AN - SCOPUS:84961133233

SP - 83

EP - 99

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -

An integrated reward and reputation mechanism for MCS preserving users’ privacy

Abstract

Access to Document

Other files and links

Fingerprint

Cite this