摘要
[研究目的]以情报信息为先导,构建大数据驱动的城市社区反恐模式,可为基层警务单位的反恐工作提供参考。[研究方法]城市社区反恐模式包含数据分析模块、数据平台驱动的业务流模块以及多部门数据联动模块三个部分。数据分析模块以反恐数据挖掘、反恐风险分析、反恐积分预警三类数据分析为基础搭建。数据平台驱动的业务流模块包含由数据分析模块对应社区反恐工作的输入输出指令和相关数据。多部门数据联动模块中构建了基层警务单位与辖区内其他部门的横向数据联动以及与上级反恐部门的纵向数据联动方式。[研究结论]大数据驱动的城市社区反恐模式可以充分利用数据资源做好社区反恐工作,将科技变为基层警力提高反恐工作的效率和针对性,进而推动构建安全城市反恐防控体系。
[Research purpose]The establishment of counter-terrorism pattern in urban communities driven by big data,taking intelligence as the guide,is conducive to provide reference for the counter-terrorism work of police units.[Research method]The pattern includes three parts:data analysis module,big data-driven business flow module,and multi-department data linkage module.The first module is built on the basis of counter-terrorism data mining,risk analysis and integral warning.The second module corresponds to input and output instructions and data between the data analysis module and community counter-terrorism work.The third module includes horizontal data linkage collaboration between basic police units and other departments,and vertical data linkage cooperation among different counter-terrorism departments.[Research conclusion]This work pattern could make full use of data resources to do a good job in community counter-terrorism,turn technology into policing power to improve the efficiency and pertinence of counter-terrorism work,and further promote the construction of a safe city in the field of counter-terrorism prevention and control system.
作者
李勇男
Li Yongnan(School of National Security,People's Public Security University of China,Beijing 100038)
出处
《情报杂志》
CSSCI
北大核心
2023年第12期106-110,7,共6页
Journal of Intelligence
基金
北京市社会科学基金项目“大数据背景下北京反恐风险特征识别及应急防范机制研究”(编号:21GLC064)的研究成果。
关键词
国家安全
反恐情报
大数据
数据联动
社区反恐
新基建
national security
counter-terrorism intelligence
big data
data linkage
counter-terrorism in community
new infrastructure development
