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智能云电视公共安全服务平台建设 被引量:1

Building a public security service platform for Smart cloud TV
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摘要 随着三网融合的推进,智能电视行业得到了迅猛发展,云电视是智能电视发展到目前的高级阶段,更强调电视终端作为平台入口及其与海量云服务资源的平滑对接,这势必将引发电视生态系统在硬件平台、操作系统、软件应用、网络云服务等多层面的信息安全问题.本文针对"行业内尚无统一有效的安全治理支撑手段"、"多源资源整合带来的内容安全问题"以及"云电视系统的开放性所引发的用户数据隐私保护威胁"的现状,构建了"智能云电视公共安全服务平台"——主要包括证书认证服务子系统、终端安全代理子系统、安全监测中心子系统以及安全测评服务子系统.该平台的建设,将提供行业级的可管控的产业生态和可信的商业环境. With the development of tri-networks, there has been a growing trend in the Smart TV industry. In particular, cloud TV has reached its highest level with widespread cloud service access. However, this has raised important security issues pertaining to Smart TV ecosystems including hardware platforms, operating systems,software applications, cloud services, etc. In this paper, we propose a Smart cloud TV public security service platform to address the lack of unified security management in the Smart TV industry. Our platform solves the content security problem when unifying resources from different parties and protects user privacy at the same time. Our platform has four implemented sub-systems, including a digital certificate authentication system, device security agent system, security monitor system, and security measurement system. Evaluation shows that our platform can provide a cutting-edge Smart TV ecosystem as well as a trusted business environment.
出处 《中国科学:信息科学》 CSCD 北大核心 2015年第10期1289-1309,共21页 Scientia Sinica(Informationis)
基金 国家自然科学基金(批准号:61202476) 中国科学院战略性先导科技专项(批准号:XDA06040502 XDA06010701)资助项目
关键词 智能云电视 安全 公共服务平台 设备证书激活 安全代理 安全评测 Smart cloud TV security public service platform device certificate activation secure agent secure assessments
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参考文献25

  • 1工业和信息化部电信研究院.移动互联网白皮书.北京:工业和信息化部电信研究院,2013. 被引量:1
  • 2何遥.智慧社区的现状与发展[J].中国公共安全,2014(2):70-75. 被引量:11
  • 3Egele M, Kruegel C, Kirda E, et al. PiOS: detecting privacy leaks in iOS applications. In: Proceedings of the 17th Annual Network and Distributed System Security Symposium. San Diego: NDSS, 2011. 被引量:1
  • 4Anupam D, Nikita B, Matthew C. Do you hear what I hear? Fingerprinting smart devices through embedded acoustic components. In: Proceedings of the ACM SIGSAC Conference on Computer and Communications Security. Scottsdale: ACM, 2014. 441-452. 被引量:1
  • 5Zhou Z, Diao W R, Liu X Y, et al. Acoustic fingerprinting revisited: generate stable device ID stealthily with inaudible sound. In: Proceedings of the ACM SIGSAC Conference on Computer and Communications Security. Scottsdale: ACM, 2014. 429-440. 被引量:1
  • 6Dey S, Roy N, Xu W, et al. AccelPrint: imperfections of accelerometers make smartphones trackable. In: Proceedings of the 20th Network and Distributed System Security Symposium. San Diego: NDSS, 2014. 1-16. 被引量:1
  • 7Felt A P, Ha E, Egelman S, et al. Android permissions: user attention, comprehension, and behavior. In: Proceedings of the 8th Symposium on Usable Privacy and Security. Washington: ACM, 2012: 3, 1-14. 被引量:1
  • 8Pang J, Creenstein B, Cummadi R, et al. 802.11 user fingerprinting. In: Proceedings of the 13th Annual International Conference on Mobile Computing and Networking. Montreal: ACM, 2007. 99-110. 被引量:1
  • 9Brik V, Banerjee S, Gruteser M, et al. Wireless device identification with radiometric signatures. In: Proceedings of the 14th ACM International Conference on Mobile Computing and Networking. San Francisco: ACM, 2008. 116-127. 被引量:1
  • 10Kohno T, Broido A, Claffy K C. Remote physical device fingerprinting. IEEE Trans Dependable Secure Comput, 2005, 2:93-108. 被引量:1

二级参考文献19

  • 1刘云生.特种数据库技术[M].北京:北京科学出版社,2000.. 被引量:3
  • 2SEIFERT C, WELCH I, KOMISARCZUK P. Identification of malicious Web pages with static heuristics [ C ]//Proc of Australasian Telecom- munication Networks and Applications Conference. 2008:91-96. 被引量:1
  • 3RICHARDSON R. 12th annual edition of the CSI computer crime and security survey[ R ]. [ S. 1. ] :Computer Security Institution ,2008. 被引量:1
  • 4McAfee threats report: fourth quarter 2010 [ R]. [ S. 1. ] : McAfee Labs,2011. 被引量:1
  • 5HAN Lan-sheng, FU Cai, ZOU De-qing, et al. Task-based behavior de- tection of illegal codes [ J ]. Mathematical and Computer Model- ling,2012,55( 1 ) :80-86. 被引量:1
  • 6WANG C,PANG J M,ZHAO R C, et al. Malware detection based on suspicious behavior identification [ C ]//Proc of the 1st International Workshop on Education Technology and Computer Science. 2009: 198- 202. 被引量:1
  • 7TIAN R,BATTEN L M,ISLAM R,et al. Differentiating malware from cleanware using behavioural analysis [ C ]//Pro~ of the 5th IEEE In- ternational Conference on Malicious and Unwanted Software. 2010:23- 30. 被引量:1
  • 8RIECK K, LASKOV P. Linear-time computation of similarity measures for sequential data [ J]. Journal of Machine Learning Research, 2008,9(6/1 ) :23-48. 被引量:1
  • 9AHMED F, HAMEED H, SHAFIQ M Z, et al. Using spatio-temporal information in API calls with machine learning algorithms for malware detection [ C ]//Proc of the 2nd ACM Workshop on Security and Artificial Intelligence. New York : ACM Press, 2009 : 55- 62. 被引量:1
  • 10SZOR P. The art of computer virus research and defense [ M ]. [ S. 1. ] : Addison-Wesley Professional ,2005. 被引量:1

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