基于机器学习建模的口令脆弱性检测

Password Vulnerability Detection based on Machine Learning Modeling

为了解决网络中的口令脆弱性评估、口令混淆检测等问题,研究基于机器学习融合告警的口令脆弱性评估方法,从大量的样本集中学习概率语言特征和文本上下文特征,通过随机森林算法和逻辑回归算法构建机器学习融合告警模型,实现了口令脆弱性的智能评估功能。将机器学习算法引入口令评估领域,大幅提高口令的评估检测能力,能够准确识别时序变化和恶意混淆的口令。

In order to solve the problems of password vulnerability assessment and password confusion detection in the network,the password vulnerability assessment method based on machine learning fusion alarm is explored.This method learns probabilistic language features and text context features from a large number of samples,and constructs machine learning fusion alarm model by using random forest algorithm and logical regression algorithm to realize the intelligent evaluation function of password vulnerability.Machine learning algorithm is introduced into the password evaluation field,which can greatly improve the ability of password evaluation and detection,and accurately identify the password with time sequence change and malicious confusion.