摘要:可信度量作为可信计算"度量、存储、报告"三大核心功能的基础，到目前为止仍未有有效的数学理论以及运行时（runtime）度量方法.其困难在于3点：一是如何建立涵盖不同主流"可信"定义的通用数学模型；二是如何依托数学模型构建运行时可信度量理论；三是如何将上述模型和理论映射到真实信息系统以形成可实践的实时度量方法.提出了一种基于无干扰的软件实时可信度量方法.首先，利用无干扰模型解释了各类主流的可信定义，表明无干扰模型可以作为可信计算通用数学模型的一个选择.其次，基于无干扰模型提出了一种软件实时可信度量理论，其基本思想是将系统调用视作原子动作，将软件真实行为α看做系统调用的序列，并基于α中所有系统调用所属安全域之间的无干扰关系计算软件理论上的预期行为β，得到α和β之后，利用无干扰等式判定两者之间是否存在偏差，从而实现对软件可信性的实时度量.最后，给出了实时可信度量算法，算法的时间复杂性为O（1）.原型实验结果表明了所提出的方法的有效性.



Abstract:Trust measurement, which is the basis of "measurement, storage, and reporting" of trusted computing, is still lack of mathematical theory and has few applications in a real-time environment thus far. The difficulty lies in three points. One is how to establish a general mathematical model that can cover different mainstream definitions of "trust"; the second is how to build a runtime trust measurement theory based on the established mathematical model; and the third is how to map the above the model and theory to real information systems, and therefore form a practical real-time measurement method. To address the above issues, a runtime software trust measurement approach is proposed. Initially, a noninterference model is leveraged to explain different mainstream definitions of trust, indicating that noninterference model can be an appropriate option of general mathematical model for trusted computing. Next, a noninterference model-based real-time trust measurement theory is presented. In the proposed trust measurement theory, a system call is processed as an atomic action, and the sequence of system calls is constructed as the real behaivior of a process. Note that every system call belongs to a security domain, and different security domains are of noninterference with each other. Therefore, after obtaining a real behavior α, the theoretically expected behavior β can be calculated based on the noninterference relations between security domains to which system calls in α belong. Once obtaining α and β, the trust of a process can be measured by determining whether two behaivors α and β deviates. Finally, a trust measurement algorithm is given. The algorithm can determine whether a process trust or not, i.e., whether the real behavior α and the theoretically expected behavior β deviates, within the time complexity of O(1). The proposed theory is also applied into real information system, and experimental results show that the proposed approach is effective and efficient.



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