The invention discloses an
intelligent equipment machine learning
safety monitoring system based on a user behavior. The
system is characterized by comprising a first-level
machine learning model oriented to the
third party intelligent equipment user behavior data and a second-level user behavior
machine learning model of an
intelligent equipment side based on a MPU
memory protection mechanism; the first-level learning model performing data cleaning on two types of data on the basis of two types of data, namely, the data of the same intelligent equipment type and the behavior data of the same individual user, by means of the user behavior data of a
third party cloud platform, determining the data and the correlation needed to use by the intelligent equipment, and determining a subject of the intelligent equipment user behavior according to the type of the intelligent equipment; the second-level user behavior
machine learning model of the intelligent equipment side based on the MPU
memory protection mechanism, the intelligent equipment side firstly using the
memory protection mechanism of the MPU to divide safety protection regions on a
safety monitoring model obtained in the first-level
machine learning model, and finally enabling a
monitoring system to effectively protect the security of the intelligent equipment and the user.