Malicious program detection method based on deep learning

The invention discloses a malicious program detection method based on deep learning, and the method comprises the following steps: S100, collecting data, and extracting features; s200, preprocessing the data; s300, designing a deep learning model; s400, training a deep learning model; s500, deploying a deep learning model; and S600, optimizing and updating the deep learning model. According to the rogue program detection method based on deep learning, malicious software can be efficiently and accurately detected, meanwhile, user privacy is protected, an advanced, reliable and efficient deep learning rogue program detection solution is provided for the field of network security, the detection accuracy and robustness are improved on the technical level, and the detection efficiency is improved. And the practical application and the user experience are remarkably improved. 本申请公开了一种基于深度学习的恶意程序检测方法，所述方法包括以下步骤：S100:收集数据,提取特征；S200:预处理数据；S300:设计深度学习模型；S400:训练深度学习模型；S500:部署深度学习模型；S600:优化与更新深度学习模型。本发明一种基于深度学习的恶意程序检测方法能