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基于双生物识别技术的DRM系统设计 被引量:2

Design of Digital Rights Management System Based on Bi-Biometric Technology
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摘要 安全有效的数字媒体内容保护方案已为当前媒体内容应用中最为迫切的技术需求。文中提出了一种新的DRM模型,该模型是基于融合了高安全性的虹膜识别和人脸识别的双子认证系统,能够稳定而准确的通过对非法用户进行访问控制来完成对数字内容使用的权限管理。首先对两种不同生物特征识别技术和DRM系统作简要的介绍,然后对提出系统作详细介绍。为了保证生物数据的安全}生,采用基于PKI安全协议。分析表明双因子认证通过组合两种不同条件来证明一个人的身份,安全性有了明显提高,提出的模型有较高的可靠性,适用于数字内容的安全分发。 Secure and efficient content protection schemes have become the most urgent technology in current media content application. A new DRM model based on highly secure iris recognition and face recognition is proposed, which can achieve the rights management of digital content exactly through the illegal user's access control. This paper first presents two biometric identification techniques and the DRM system, and then introduces the proposed system in detail. To ensure the security of the biometric data, a protocol based on PKI is proposed. Analysis shows the security of this system is improved remarkably by the Double-Biometric technology of identifying a person's identity by combining two different conditions. The proposed model is highly reliable and applicable to the secure distribution of digital content.
出处 《电子科技》 2008年第7期57-63,共7页 Electronic Science and Technology
基金 国家自然科学基金(60672112)
关键词 数字版权管理 数字内容 生物测定学 虹膜识别 人脸识别 PKI DRM digital content biometric iris recognition face recognition PKI
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  • 1[1]Glossary of biometrics terms [R].1998,Association for biometrics(AfB),Intemational Computer Security Association (ICSA).
  • 2[2]R Chellappa,et al.Humnan and machine recognition of face:a survey[J].Proc.IEEE,1995,83 (5):705-740.
  • 3[3]R Brunelli,T Poggio.Face recognition:features versus templates [J].IEEE Trans.PAMI,1993,15(10):1042-1052.
  • 4[4]D L Swets,J Weng.Using discriminant eigenfeatures for image retrieval[J].IEEE Trans.PAMI,1996,18 (8):831-836.
  • 5[5]B Moghaddam,et al.Probabilistic visual recognition for object recognition [J].IEEE Trans.PAMI,1997,19(7) :696-710.
  • 6[6]S Y Lee,et al.Recognition of humman front faces using knowledgebased feature extraction and neunofuzzy algorithm [J].Pattern Recognition,1996,29(11):1863-1876.
  • 7[7]S Lawtonce,et al.Face recognition:a convolutional neural-network approach [J].IEEE Trans.NN,1997,8(1):98-113.
  • 8[9]J Zhang,et al.Face recognition:eigenface,elastic matching,and neural nets [J].Proc.IEEE,1997,85(9):1422-1435.
  • 9[10]L Wiskott,et al.Face recognition by elastic bunch graph matching [J].IEEE Trans.PAMI.1997,19(6) :775-779.
  • 10[11]N Ratha,et al.A real-time matching system for large fingerprint database [J].IEEE Trans.PAMI,1996,18(8) :799-813.

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