云计算环境下软件异常区域检测模型仿真

Detection Model Simulation of Software Anomaly Area under Cloud Computing Environment

在云计算环境下针对软件异常区域进行检测的过程中,软件局部区域会遭受恶意攻击,传统的检测算法受到数据冗余的影响,导致检测效率准确性较低。提出基于关键特征映射算法的云计算环境下软件异常区域检测方法。根据最小二乘法相关原理,提取云计算环境下软件异常区域攻击特征,利用主成分分析法,提取主要攻击特征,删除大量的冗余特征,降低计算的复杂性。建立关键特征映射模型,完成云计算环境下软件异常区域检测。实验结果表明,利用改进算法进行云计算环境下软件异常区域检测,能够极大的提高检测的准确性。

A key feature mapping algorithm is proposed based on software anomaly area detection method in cloud computing environment. According to the principle of least square method, the attack characteristics of software a- nomaly area are extracted under the cloud computing environment, the main attack feature is extracted by using prin- cipal component analysis （pea）, a large number of redundant features are deleted, and the complexity of calculation is reduced. A key feature mapping model is established, and the detection of software anomaly area is completed in the cloud computing environment. The experimental results show that the improved algorithm can greatly improve the accuracy of detection.