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Security challenges for the mobile crowdsensing network |
WANG Zhengqi |
National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China |
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Abstract: As a new paradigm of sensing in the Internet of Things, the mobile crowdsensing network takes advantage of ubiquitous sensing device within a specific range to collect sensing data of individuals, situations and environments for a variety of applications. This paper introduces the current application development of the mobile crowdsensing network, analyzes the development trend of intelligent transportation services, infrastructure and municipal management, environmental monitoring, early warning, social relations and public safety, public health and medical services. Then it proposes a number of security challenges faced by the mobile crowdsensing network in the future, including user privacy protection, security of the sensing data and platform, the improvement of sensing quality and efficiency, and resources consumption optimization.
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Received: 24 November 2015
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[1] Ganti R K, Ye F, Lei H. Mobile crowdsensing: Current state and future challenges[J]. IEEE Communications Magazine, 2011, 49(11): 32-39.
[2] 刘云浩. 群智感知计算[J]. 中国计算机学会通讯, 2012, 8(10): 38-41. Liu Yunhao. Crowd sourcing computing[J]. Communications of the CCF, 2012, 8(10): 38-41.
[3] Ma H, Zhao D, Yuan P. Opportunities in mobile crowd sensing. Com-mun[J]. IEEE Communications Magazine, 2014, 52(8):. 29-35.
[4] Howe J. The rise of crowdsourcing[J]. Wired Mag, 2006, 14(6): 1-4.
[5] 赵东. 移动群智感知网络中数据收集与激励机制研究[D]. 北京: 北京 邮电大学, 2014. Zhao Dong. Research on data collection and incentive mechanisms in mobile crowd sensing networks[D]. Beijing: Beijing University of Posts and Telecommunications, 2014.
[6] Scaffidi C, Myers B, Shaw M. Intelligently creating and recommending reusable reformatting rules[C]. The 14th International Conference on In-telligent User Interfaces, Hong Kong, China, Feb 7-10, 2010.
[7] Hacker S, von Ahn L. Matchin: Eliciting user preferences with an on-line game[C]. The 27th International Conference on Human Factors in Computing Systems, CHI 2009, Boston, MA, USA, April 4-9, 2009. SI-GIR'09
[8] Ma H, Chandrasekar R, Quirk C, et al. Improving search engines using human computation games[C]. The 18th ACM Conference on Informa-tion and Knowledge Management. Boston, Massachusetts, USA, July 19-23, 2009.
[9] Shahabi C. Towards a generic framework for trustworthy spatial crowd-sourcing[C]. The 12th International ACM Workshop on Data Engineer-ing for Wireless and Mobile Acess, New York, USA, June 23, 2013.
[10] Thiagarajan A, Ravindranath L, LaCurts K, et al. VTrack: Accurate, energy-aware road traffic delay estimation using mobile phones[C]. The 7th International Conference on Embedded Networked Sensor Sys-tems, SenSys 2009, Berkeley, California, USA, November 4-6, 2009.
[11] Goldman J, Shilton K, Burke J, et al. Participatory sensing: A citizenpowered approach to illuminating the patterns that shape our world[R]. Foresight & Governance Project, White Paper, 2009: 1-15.
[12] Mohan P, Padmanabhan V N, Ramjee R. Nericell: Rich monitoring of road and traffic conditions using mobile smartphones[C]. The 6th Inter-national Conference on Embedded Networked Sensor Systems, SenSys 2008, Raleigh, NC, USA, November 5-7, 2008.
[13] Ni L, Liu Y, Lau Y, et al. LANDMARC: Indoor location sensing using active RFID[J]. Wireless Networks, 2004, 10(6): 701-710.
[14] Dutta P, Aoki P M, Kumar N, et al. Common sense: Participatory ur-ban sensing using a network of handheld air quality monitors[C]. The 7th International Conference on Embedded Networked Sensor Sys-tems, SenSys 2009, Berkeley, California, USA, November 4-6, 2009.
[15] 张佳凡, 郭斌, 路新江, 等. 基于移动群智数据的城市热点事件感知 方法[J]. 计算机科学, 2015, 42(6A): 5-9. Zhang Jiafan, Guo Bin, Lu Xinjiang, et al. Approach for urban popular event detection using mobile crowdsourced data[J]. Computer Science, 2015, 42(6A): 5-9. |
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