Development Of Security Intelligence Research And Judgment System Based On Big Data Analysis

With the development of society,the increasing frequency of population movements,the diversity and complexity of the social security situation,the criminal methods of crimes appear more and more concealed and highly intelligent.Today,the country is vigorously advocating the construction of smart cities and safe cities,which puts higher demands on public security measures under the new situation.At present,most areas still stay in the traditional form of artificial judgment when conducting public security work,which is time-consuming,labor-intensive and inefficient,lacking accuracy and predictability.Of course,some security agencies have tried to establish a comprehensive security management platform.However,for public security intelligence data,most of them can only do general statistical analysis,lack of correlation analysis and mining analysis with intelligence-related information,and it is difficult to find hidden in intelligence data,so it is difficult to achieve precise prevention.This thesis is based on the wisdom and safe community platform,and proposes to build a public security intelligence research and judgment system,mainly to analyze and judge the daily intelligence data of the community to maintain a good public security environment.Because of the huge complex data and many index factors in the community,this paper draws on the technology of big data analysis and builds a system platform using Java Web technology to conduct intelligence research and judgment operations.The paper mainly discusses the requirements,key technologies,detailed design and implementation of the system one by one,and develops each database and function module.Through the B/S architecture,the intelligence data collection,query statistics,time and space analysis,contrast or string,and use ECharts to visualize the data,and finally completed the development of the security intelligence research and judgment system.It has been well applied in the actual community security,and played a practical effect.This paper has the following two characteristics:(1)The system achieves automatic association string functions of cases.(2)Applying the ARIMA model to the prediction of the time series of cases.