基于自学习多维参数可信安全度量模型研究

针对可信度量现存问题,依据软件安全保护原则提出通过融合多方度量因子建立综合的可信度量模型——随机抽取划分序列策略模型。该模型兼顾了软件安全度需求系数、软件安全度评估系数及软件执行所需资源开销系数等多方因素,摒弃了传统单一的度量方法,建立了综合性的可信度量策略及构造方法,兼顾了多方面安全需求问题,并且实现了细粒度完整性检验,降低了可信度量的运算开销。

Trusted Measurement Model of Multidimension Parameter Based on Self-learning

To solve trusted measurement, a trusted measurement model of multidimension parameter (called Random Division Sequence Model, D^R is given through the integration of multi-factor based on the software security protection principles. D^R takes into account software security level factor, software security assessment factor and the required resources of software operation factor, which abandons the traditional single measurement methods and establishes a comprehensive trusted measurement model by giving consideration to various security requirements. D^R achieves a fine-grained integrity measurement, and reduces operation costs.