User behavior safety early warning method and system for electric power monitoring system

Abstract

The invention discloses a user behavior safety early warning method and system for an electric power monitoring system. The method comprises the following steps: acquiring a safety monitoring log of the electric power monitoring system; extracting user operation information based on the collected security monitoring log, and performing user behavior data characterization processing on the user operation information; and inputting the obtained user behavior characteristic data into a pre-trained machine learning model to finally obtain early warning prompt information based on the user behaviorsafety level. The invention provides a safety early warning method based on user behavior safety risk grading, and aims to improve the effectiveness and accuracy of data association analysis of a power monitoring system. According to the user behavior safety grading method provided by the invention, the judgment of the risk level of the user behavior is achieved, the corresponding alarm is givenon the electric power monitoring system, the field monitoring personnel is timely reminded to carry out the alarm operation in time, and the safety of the electric power monitoring system and the realization of the electric power safety monitoring function are ensured.

Description

technical field [0001] The invention belongs to the technical field of power system safety monitoring, and in particular relates to a user behavior safety early warning method and system of a power monitoring system. Background technique [0002] In addition to traditional behaviors that endanger network security such as hacker attacks and virus intrusions, behaviors that violate security policies caused by abnormal operations of internal users also pose a great threat to the safe operation of the system. For these abnormal or illegal operations, traditional security measures such as firewalls are not effective in detecting them. [0003] Power systems generate large amounts of data every day. Safety assessment is an important part of power system secondary system safety and protection. However, the current security protection products of the power monitoring system have formed a security island, and the products cannot be effectively connected in series, and the security ...

AI Technical Summary

Problems solved by technology

However, the current security protection products of the power monitoring system have formed a security island, and the products cannot be effectively connected in series, and the security protection measures for security risks cannot be informed to the entire network.

It is impossible to effectively prevent known risks; the current security protection methods of power monitoring systems are based on rules and historical data, and the correlation between data is relatively low. It is impossible to effectively analyze a large amount of real-time data, and the early warning results are extremely large. The extent depends on the rules of their respective security products, and there is no effective analysis method for unknown threats; the current power monitoring system cannot link security policies in real time based on alarm results, and cannot issue targeted security policies based on current security risks. Security protection There is hysteresis; the current power monitoring system lacks an effective safety evaluation system, and the safety protection work has not entered a virtuous circle, only passive defense for safety protection issues

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