【摘要】 通过数据预测犯罪有着悠久的历史，从一百多年前的犯罪制图到近年来西方的预测性警务，再到国内通信运营商运用大数据技术对电信网络诈骗犯罪进行预警，显现出数据预测犯罪技术日趋成熟。情境预防理论所提倡的通过控制犯罪要素来预防犯罪的理念，启示需要对电信网络诈骗犯罪涉及的犯罪要素构建类罪模型。电信网络诈骗犯罪的大数据预警实践经验丰富了情境预防理论的理论框架。在构建电信网络诈骗犯罪模型基础上，提出电信网络诈骗犯罪的大数据预警模型，基于犯罪信息流可运用大数据技术对虚假信息从源头进行发现、从传播过程进行识别、从终端设备进行拦截；基于犯罪资金流，可通过建立若干适应诈骗手法动态变化的疑似被害人资金账户监测模型，实现资金流数据预警电信网络诈骗犯罪的目标。更多还原

【Abstract】 Crime prediction by empirical data has a long history from crime mapping more than 100 years ago to the predictive policing in the past decadein the western countries,and then to the use of big data technology by domestic telecom operators to warn telecom network fraud crimes,which shows that the technology of data prediction of crime is becoming more and more comprehensive.Situational crime prevention advocates the concept of preventing crime by controlling the elements of crime,which reveals that it is necessary to construct a crime model for the elements of crime involved in telecom network fraud.The early warning practice oftelecom network fraud by big data has enriched the theoretical framework of situational prevention theory.On the basisofthe telecom network fraudmodel,the big data early warning model of telecom network fraud crime is proposed,and it is explained in details that based on criminal information flow,big data technology can be used to detect false information from the source,identify them from the transmission process,and intercept it from terminal equipment.Based on the criminal capital flow,a number of monitoring models of suspected victim’s capital account that adapt to the dynamic changes of fraud methods can be established to realize the goal of early-warning telecom network fraud based on the capital flow data.更多还原