The invention discloses an
Internet of Things malicious traffic detection method and device and a storage medium, and the method comprises the following steps: S1, collecting malicious traffic data of
Internet of Things equipment, and classifying and constructing a malicious traffic sample
library; s2, converting the malicious traffic data into a
grayscale image by adopting a text imaging method, and performing normalization,
noise reduction and feature enhancement; s3, extracting local binary pattern features, global image features and high-order local automatic correction features, and constructing a malicious traffic feature
database; s4, training the malicious traffic detection model by adopting a space-time
capsule Transform, extracting space and time features, and performing classification training; s5, collecting real-time traffic data, calculating an abnormal
score by using the trained model, and judging a traffic category; and S6, sending a detection result to a
command and control server, triggering an alarm, and sending a blocking or isolating instruction to the attacked device. The method improves the accuracy and real-time performance of malicious traffic detection, and is suitable for
security monitoring and protection of
the Internet of Things.