学术聚焦

移动群智感知网络发展面临安全挑战

  • 王钲淇
展开
  • 国家计算机网络应急技术处理协调中心, 北京100029
王钲淇,助理工程师,研究方向为网络信息安全,电子信箱:tcwjz861107@126.com

收稿日期: 2015-11-24

  修回日期: 2015-12-10

  网络出版日期: 2016-01-07

Security challenges for the mobile crowdsensing network

  • WANG Zhengqi
Expand
  • National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China

Received date: 2015-11-24

  Revised date: 2015-12-10

  Online published: 2016-01-07

摘要

作为一种全新的物联网感知模式,移动群智感知网络通过普适感知设备采集特定范围内的个体、情景、环境感知数据,完成复杂的泛在深度社会感知任务并提供丰富应用。介绍了移动群智感知网络当前的应用发展状况,分析了在智能交通服务、基础设施和市政管理服务、环境监测预警、社会关系与公共安全、公众健康和医疗服务等方面的发展趋势。提出了一些移动群智感知网络在未来所面临的安全挑战,分析了用户隐私保护、感知数据和平台的安全性、感知质效提升和资源优化利用方面面临的挑战。

本文引用格式

王钲淇 . 移动群智感知网络发展面临安全挑战[J]. 科技导报, 2015 , 33(24) : 114 -117 . DOI: 10.3981/j.issn.1000-7857.2015.24.018

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.

参考文献

[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.
文章导航

/