基于区间数据场景级属性可信评测的检测能力分析

Analysis of detectability for trusted evaluation based on scene-level attribute of interval data

如今的可信计算机仅可以确保系统资源静态安全,但是在运行系统后,其软件行为可信性决定着终端计算机可信性。基于软件运行动态可信性,将基于区间数据场景级属性可信测评模型引入以往软件行为模型中,通过检查点属性分级,简化检查点可信评价,并结合检查点场景级客观赋权和属性主观分级赋权,以构建场景级属性可信模型的方式可信测评区间数据场景及属性。结果发现,基于分级属性减少了对比阈值的次数,由此表明,基于区间数据场景级属性可信评测攻击检测能力比较高,而且具有有效性。

Trusted computer can ensure static state security of system resource only,but the terminal computer credibility is determined by software behavior credibility after operating the system. Based on the dynamic credibility of software operation,the trusted evaluation model on the basis of the scene-level attribute of interval data is introduced into the previous software behavior model. The trusted evaluation of the checkpoint is simplified by attribute classification of the checkpoint. In combination with the objective weighting of the checkpoint scene-level and the subjective classification weighting of the attribute,the interval data scene and the attribute are evaluated by constructing the trusted model of scene-level attribute. It is found that the frequency of contrast threshold can be reduced by attribute classification,which shows that the detectability of trusted evaluation attack for interval data scene-level attribute is relatively high,and has validity.