Data security abnormity monitoring method and system in public information platform

Abstract

The invention discloses a data security abnormity monitoring method and system in a public information platform. The system comprises a data layer responsible for data collection, an analysis layer for three-level data analysis and a presentation layer for visibility presentation and threat prediction. The data collection of the data layer adopts a multi-source data collection method; the presentation layer mainly afterwards applies a visibility technique, carries out visibility presentation to security threats and helps a decision maker to know the security threat tendency and dynamic states of the system visually; and an executor can know concrete details through a multi-layer pull-down form. According to the method and the system provided by the invention, a manager center processes, analyzes and presents collected data in a clustering mode; the system is of B / S architecture; different personnel can carry out operations such as querying, processing and analyzing to the data through an IE or other browsers; related managers can carry out graphical presentation, know the security conditions of the data visually, perceive the development dynamic states of the data security and dispose timely after an event is generated.

Description

technical field

[0001] The invention relates to the field of data security, in particular to a data security anomaly monitoring method and system in a public information platform. Background technique

[0002] Traditional firewall and other technologies have existed for 20 to 30 years. Although they have been changing, the essence and structure have not changed. In the future, they will not be able to adapt to the security requirements of the big data environment. With the emergence of application models such as cloud computing and big data, the security architecture will also undergo tremendous changes. For example, users are using smart devices, all data is stored in the cloud, and all information is stored centrally. How to ensure the safe use of this information depends on big data analysis and machine learning modeling. Therefore, driven by the collection, processing and analysis technology of big data, it helps enterprises to automatically detect internal and external...

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