文献类型：期刊文献

中文题名：基于大数据的危害国家安全犯罪预测侦查研究

英文题名：Research on Predictive Investigation of Crimes of Endangering State Security Based on Big Data

作者：丁华宇[1];孟念[1]

第一作者：丁华宇

机构：[1]河南财经政法大学刑事司法学院,河南郑州450046

第一机构：河南财经政法大学刑事司法学院|河南财经政法大学法学院

年份：2024

卷号：33

期号：2

起止页码：96-105

中文期刊名：河南警察学院学报

外文期刊名：Journal of Henan Police College

基金：国家社会科学基金年度项目“数据刑事合规问题研究”(22BFX064);2021年河南省哲学社会科学规划项目“网络诈骗犯罪的刑法规制研究”(2021BFX008)。

语种：中文

中文关键词：大数据;危害国家安全犯罪;预测侦查;侦查模式

外文关键词：big data;crimes of endangering state security;predictive investigation;investigation mode

摘要：由算法所主导的预测性侦查正成为大数据侦查的新分支。危害国家安全犯罪的预测侦查更加强调干预节点的前移和涉危群体或人员的预判,而这一节点已前移至涉危线索发现之前。以大数据为基础的预测性侦查模式可以塑造国家安全维护新思维、实现涉危情报信息的整合共享、有效判别罪与非罪、此罪与彼罪及确保涉危证据留痕与追溯。涉危领域的预测侦查有着一套固有的流程模型,其有效运行依赖涉危情报数据可视化开发和利用、涉危数据融合共享的双向推进、涉危重点群体或人员的分级确定和侦查等予以保障。在大数据预测的运行过程中,需要秉承尊重隐私原则、坚守算法透明原则、坚持“人机共治”,以应对大数据使用所带来的风险和挑战。
Predictive investigation led by algorithms is becoming a new branch of big data investigation. Predictive investigation of crimes of endangering state security places more emphasis on the forward movement of the intervention node and the prediction of groups or persons at risk, and this node has been moved forward before the discovery of clues related to risks. The predictive investigation mode based on big data can shape a new mindset of national security maintenance, realize the integration and sharing of hazardous intelligence information, effectively distinguish between crime and non-crime, this crime and that crime, and ensure that hazardous evidence can be traced or traced back. Predictive investigation in the field of danger has a set of inherent process model, and its effective operation relies on the development and utilization of danger-related intelligence data visualization, two-way promotion of the integration and sharing of danger-related data, and the hierarchical identification and investigation of key groups or persons in danger to be guaranteed. In the operation of big data prediction, it is necessary to respect the principle of privacy, adhere to the principle of algorithmic transparency, and pursue the principle of "human-computer co-rule", in order to cope with the risks and challenges brought about by the use of big data.