Reputation and Reward: Two Sides of the Same Bitcoin

In Mobile Crowd Sensing (MCS), the power of the crowd, jointly with the sensing capabilities of the smartphones they wear, provides a new paradigm for data sensing. Scenarios involving user behavior or those that rely on user mobility are examples where standard sensor networks may not be suitable, and MCS provides an interesting solution. However, including human participation in sensing tasks presents numerous and unique research challenges. In this paper, we analyze three of the most important: user participation, data sensing quality and user anonymity. We tackle the three as a whole, since all of them are strongly correlated. As a result, we present PaySense, a general framework that incentivizes user participation and provides a mechanism to validate the quality of collected data based on the users’ reputation. All such features are performed in a privacy-preserving way by using the Bitcoin cryptocurrency. Rather than a theoretical one, our framework has been implemented, and it is ready to be deployed and complement any existing MCS system.

[1]  Iordanis Koutsopoulos,et al.  Optimal incentive-driven design of participatory sensing systems , 2013, 2013 Proceedings IEEE INFOCOM.

[2]  Minho Shin,et al.  Location Privacy for Mobile Crowd Sensing through Population Mapping † , 2015, Sensors.

[3]  Emiliano Miluzzo,et al.  Crowdsensing the speaker count in the wild: implications and applications , 2014, IEEE Communications Magazine.

[4]  Paul Resnick,et al.  Reputation systems , 2000, CACM.

[5]  Audun Jøsang,et al.  A survey of trust and reputation systems for online service provision , 2007, Decis. Support Syst..

[6]  Qinghua Li,et al.  Providing privacy-aware incentives for mobile sensing , 2013, 2013 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[7]  Wanlei Zhou,et al.  Network and system security , 2009, J. Netw. Comput. Appl..

[8]  Helena Rifà-Pous,et al.  Computational and Energy Costs of Cryptographic Algorithms on Handheld Devices , 2011, Future Internet.

[9]  Kin K. Leung,et al.  A Survey of Incentive Mechanisms for Participatory Sensing , 2015, IEEE Communications Surveys & Tutorials.

[10]  Jordi Herrera-Joancomartí,et al.  When users become sensors: can we trust their readings? , 2015, Int. J. Commun. Syst..

[11]  Björn Scheuermann,et al.  Bitcoin and Beyond: A Technical Survey on Decentralized Digital Currencies , 2016, IEEE Communications Surveys & Tutorials.

[12]  Paolo Bellavista,et al.  Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience , 2015, Sensors.

[13]  Helena Rif Computational and Energy Costs of Cryptographic Algorithms on Handheld Devices , 2011 .

[14]  Fan Ye,et al.  Mobile crowdsensing: current state and future challenges , 2011, IEEE Communications Magazine.

[15]  Sung-Ju Lee,et al.  MCNet: Crowdsourcing wireless performance measurements through the eyes of mobile devices , 2014, IEEE Communications Magazine.

[16]  Margot Brereton,et al.  Designing participation in agile ridesharing with mobile social software , 2009, OZCHI '09.

[17]  Luís E. T. Rodrigues,et al.  A Framework to Provide Anonymity in Reputation Systems , 2006, 2006 Third Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services.

[18]  Tal Malkin,et al.  Reputation Systems for Anonymous Networks , 2008, Privacy Enhancing Technologies.

[19]  Salil S. Kanhere,et al.  A survey on privacy in mobile participatory sensing applications , 2011, J. Syst. Softw..

[20]  Andrew Raij,et al.  A Survey of Incentive Techniques for Mobile Crowd Sensing , 2015, IEEE Internet of Things Journal.

[21]  Salil S. Kanhere,et al.  A Reputation Framework for Social Participatory Sensing Systems , 2014, Mob. Networks Appl..

[22]  Jeremy Clark,et al.  Mixcoin: Anonymity for Bitcoin with Accountable Mixes , 2014, Financial Cryptography.

[23]  Fergal Reid,et al.  An Analysis of Anonymity in the Bitcoin System , 2011, PASSAT 2011.

[24]  Mirco Musolesi,et al.  Urban sensing systems: opportunistic or participatory? , 2008, HotMobile '08.

[25]  Emiliano Miluzzo,et al.  The BikeNet mobile sensing system for cyclist experience mapping , 2007, SenSys '07.

[26]  Jeremy Clark,et al.  Anonymity for Bitcoin with accountable mixes ( Full version ) , 2014 .

[27]  Brian Neil Levine,et al.  Sybil-Resistant Mixing for Bitcoin , 2014, WPES.

[28]  Y. de Montjoye,et al.  Unique in the shopping mall: On the reidentifiability of credit card metadata , 2015, Science.

[29]  Ramachandran Ramjee,et al.  Nericell: rich monitoring of road and traffic conditions using mobile smartphones , 2008, SenSys '08.

[30]  Sheng Zhong,et al.  On designing incentive-compatible routing and forwarding protocols in wireless ad-hoc networks , 2006, Wirel. Networks.

[31]  Krzysztof Grochla,et al.  Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks , 2015, Sensors.

[32]  Allison Woodruff,et al.  Common Sense: participatory urban sensing using a network of handheld air quality monitors , 2009, SenSys '09.

[33]  Xi Fang,et al.  Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing , 2012, Mobicom '12.

[34]  Salil S. Kanhere,et al.  IncogniSense: An anonymity-preserving reputation framework for participatory sensing applications , 2012, 2012 IEEE International Conference on Pervasive Computing and Communications.

[35]  Miguel A. Labrador,et al.  Privacy, quality of information, and energy consumption in Participatory Sensing systems , 2014, 2014 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[36]  Ioannis Krontiris,et al.  Participatory Sensing: The Tension Between Social Translucence and Privacy , 2011 .

[37]  Stefan Katzenbeisser,et al.  Structure and Anonymity of the Bitcoin Transaction Graph , 2013, Future Internet.

[38]  Miguel A. Labrador,et al.  A location-based incentive mechanism for participatory sensing systems with budget constraints , 2012, 2012 IEEE International Conference on Pervasive Computing and Communications.