一种基于机器学习的等级保护自动测评方法

An Automatic Assessment Method for Classified Protection Based on Machine Learning

自我国网络安全等级保护进入2.0时代以来,等级测评方法发展迅猛,但在效率和准确性上仍有待提高。提出一种利用机器学习的自动测评方法。该方法利用Logistic回归算法和线性回归算法对数据例子进行有监督学习,实现了对被测系统的各测评项进行自动分类和辅助评分,有助于提升等级保护测评的效率和准确性。

Since the classified protection of cybersecurity in China entered the 2.0 era, classified assessment methods have developed rapidly. However, it can be continually improved in efficiency and accuracy. An automatic assessment method based on machine learning is proposed. In this method, Logistic regression algorithm and liner regression algorithm are used to carry out the supervised learning of data examples. The method achieves the automatically classification and auxiliary scoring of each assessment item of the system under test and is helpful to improve the efficiency and accuracy of classified protection assessment.