Hardened Registration Process for Participatory Sensing

Participatory sensing systems need to gather information from a large number of participants. However, the openness of the system is a double-edged sword: by allowing practically any user to join, the system can be abused by an attacker who introduces a large number of virtual devices. This poster proposes a hardened registration process for Participatory Sensing to raise the bar: registrations are screened through a number of defensive measures, towards rejecting spurious registrations that do not correspond to actual devices. This deprives an adversary from a relatively easy take-over and, at the same time, allows a flexible and open registration process. The defensive measures are incorporated in the participatory sensing application.

[1]  Vijayan Sugumaran,et al.  Participatory sensing-based semantic and spatial analysis of urban emergency events using mobile social media , 2016, EURASIP J. Wirel. Commun. Netw..

[2]  Katherine A Johnson,et al.  Real Life Science with Dandelions and Project BudBurst , 2016, Journal of microbiology & biology education.

[3]  Claudio Soriente,et al.  Participatory privacy: Enabling privacy in participatory sensing , 2012, IEEE Network.

[4]  Konstantin Beznosov,et al.  Android Rooting: Methods, Detection, and Evasion , 2015, SPSM@CCS.

[5]  Long Nguyen-Vu,et al.  Android Rooting: An Arms Race between Evasion and Detection , 2017, Secur. Commun. Networks.

[6]  Mo Li,et al.  A Participatory Urban Traffic Monitoring System: The Power of Bus Riders , 2017, IEEE Transactions on Intelligent Transportation Systems.

[7]  Valérie Issarny,et al.  Probabilistic registration for large-scale mobile participatory sensing , 2013, 2013 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[8]  Andrei Vasilateanu,et al.  Environment crowd-sensing for asthma management , 2015, 2015 E-Health and Bioengineering Conference (EHB).

[9]  Davide Brunelli,et al.  Wireless Sensor Networks , 2012, Lecture Notes in Computer Science.

[10]  Nicolas Christin,et al.  Evading android runtime analysis via sandbox detection , 2014, AsiaCCS.

[11]  Ben Y. Zhao,et al.  Ghost Riders: Sybil Attacks on Crowdsourced Mobile Mapping Services , 2018, IEEE/ACM Transactions on Networking.

[12]  S. Pavithra,et al.  Secure voting system through SMS and using smart phone application , 2017, 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET).

[13]  Vittorio Loreto,et al.  Participatory Patterns in an International Air Quality Monitoring Initiative , 2015, PloS one.

[14]  Jalil Shokouh.  Detecting GNSS Attacks on Smartphones , 2013 .

[15]  Kaoru Sezaki,et al.  User Participatory Sensing for Disaster Detection and Mitigation in Urban Environments , 2016, HCI.

[16]  Jukka Riekki,et al.  Mobile crowdsensing with mobile agents , 2015, Autonomous Agents and Multi-Agent Systems.

[17]  Mo Li,et al.  Smart traffic monitoring with participatory sensing , 2013, SenSys '13.

[18]  Yunhao Liu,et al.  PLP: Protecting Location Privacy Against Correlation Analyze Attack in Crowdsensing , 2017, IEEE Transactions on Mobile Computing.

[19]  Deborah Estrin,et al.  Recruitment Framework for Participatory Sensing Data Collections , 2010, Pervasive.

[20]  Mark H. Hansen,et al.  Participatory Sensing: A Citizen-Powered Approach to Illuminating the Patterns that Shape our World , 2009 .