WIRE AND WIRELESS ACCESS POINT FOR ANALYZING ABNORMAL ACTION BASED ON MACHINE LEARNING AND METHOD THEREOF

摘要

The present invention repeatedly learns the normal behavior and the abnormal behavior type using the wireless signal and the status information transmitted and received through the wireless router, detects and analyzes the state and the wireless signal of the wireless router, The present invention relates to a router and method for analyzing abnormal behavior based on machine learning that can be blocked. The wired / wireless router for analyzing an abnormal behavior based on the machine learning based on the present invention is a wired / wireless router that repeatedly learns the normal behavior and the abnormal behavior pattern of the wired / wireless router and determines whether the wired / An information analyzer for periodically collecting wireless signals transmitted and received by the wireless router and status information of the wireless router and analyzing the collected wireless signals and status information to determine whether the operation of the router is abnormal; And a security processing unit for performing a security policy when the operation of the wireless router is an abnormal operation. The information analyzing unit analyzes the collected wireless signal and status information to analyze whether the wireless signal and the status information are abnormal, In conjunction with a machine learning engine that repeatedly learns, .