基于物联网的身份认证云计算平台研究

With the rapid development of the communication technology and the Internet, the physical and virtual space for humans is continuously expanding. Thus, the society's requirements on the accuracy, security, and practicality of the human identity authentication is becoming larger and larger. At present, the Identity authentication system has some disadvantages due to different locations, such as the difficulty to collect and transmit biological features, the slow speed for database construction and identity comparison. The usage of IOT technology and Cloud computing platform can solve the above problems. This specific research project composes of five parts: (1) Build the system structure model for identity feature extraction systems using sensors and in combination with mobile phone terminals (2) Build the massive signature cloud computing database; (3) Take the Identity authentication as the core of cloud services protocol, and proposes the multi-biometric feature extraction and fusion mechanism in the IOT and Cloud Computing environments. Provide the trusted measurement and score for identity authentication. Solve the problem of embedded recognition of the software performance, scale, and generalization in mobile computing. (4) Build the IOT perception information fusion model and method of calculating, resolving incomplete information perception, integration, and adaptation issues.(5) Propose the modeling method for the dynamic system environments. Provide the software platforms for the automatic acquisition and understanding of environmental information, and give self-adaptation problem solving methods. Solve the dynamic cloud services adaption problems in the dynamic system environment.

随着通信技术和互联网的飞速发展，人类物理和虚拟活动空间不断扩大，社会对于人类自身身份认证的准确性、安全性和实用性提出更高要求。但目前身份认证系统由于异地离散，造成生物特征采集和传输困难，建库和比对计算速度慢。采用物联网技术及云计算平台可解决上述问题，具体包括：(1) 建立以身份特征提取传感器结合手机为终端的物联网体系结构模型；(2) 建立海量特征码的云计算数据库；(3) 以身份认证为核心的云服务协议，提出物联网与云计算环境下的多模态生物特征提取与融合机理，提供身份认证的可信度量与评测的方法，解决移动计算中嵌入式识别软件的性能、规模与通用性等问题；(4) 建立对物联网感知信息进行融合计算的模型和方法，解决不完备感知信息的整合适配问题；(5) 提出系统环境动态问题域建模、软件平台对环境信息的自动获取和理解、自适应求解的方法，解决动态系统环境中的云服务适应问题。

项目立项以来，项目组成员通过理论研究与实际开发，已取得一系列实质性的成果，研究工作主要为： 建立了以身份特征提取传感器结合手机为终端的物联网体系结构模型，建立了海量特征码的云计算数据库。提出了物联网与云计算环境下的多模态生物特征提取与融合机理，提供身份认证的可信度量与评测的方法。解决了移动计算中嵌入式识别软件的性能、规模与通用性等问题。开发了基于物联网（无线网络)的手机及移动终端的指纹采集、识别和比对的软硬件系统，研发了物联网感知信息融合计算软件，解决了不完备感知信息的整合适配问题。提出了以身份认证为核心的云服务协议， 解决了系统环境动态问题域建模、软件平台对环境信息的自动获取和理解、自适应求解的方法，解决动态系统环境中的云服务适应等问题。尤其解决了不同操作系统下数据库在云环境下的兼容问题，私云与公云之间数据库的配置等实际应用问题，对基于无线网络的身份认证（指纹识别）的理论研究与应用做了有效的工作。项目组成员已发表论文43篇，获得软件著作权9项，获得专利3项。获省部级奖2项。