面向多源异构数据融合的反诈大数据平台建设路径研究

Research on the Construction Path of Anti-fraud Big Data Platform Based on Multi-Source Heterogeneous Data Fusion

当前涉诈数据来源广泛、结构多样,实现多源异构数据融合是提升反诈大数据平台建设水平的必要条件。针对面向多源异构数据融合的反诈大数据平台建设需求,在总体设计上提出了由数据、功能、协同三大中心组成的分层耦合逻辑系统框架;在实现路径上,首先,基于联盟链的分布式数据融合系统作为技术支撑以实现数据共享和隐私保障;其次,引入综合集成研讨厅模式为具体方案形成落地提供动态循环研判与知识利用的思维模式和工作流程。最后,以“时间维—对象维—性质维”框架构建了标准体系,从模块应用和质量保证两方面对系统运行过程形成规范约束力。

The current landscape of fraudulent data is characterized by a wide range of sources and structural diversity.Achieving multi-source heterogeneous data fusion is a necessary condition for improving the level of anti-fraud big data platform construction.To meet the needs of constructing anti-fraud big data platforms that are oriented towards multi-source heterogeneous data fusion,a layered and coupled logical system framework consisting of three centers-data,function,and collaboration-is proposed in the overall design.In terms of implementation,a distributed data fusion system based on consortium blockchain is proposed as a technical support to achieve data sharing and privacy protection.Secondly,the hall for workshop of meta-synthetic engineering model is introduced as a specific solution to provide a dynamic and iterative thinking mode and workflow for knowledge utilization.Finally,a standard system is constructed based on the“time dimension-object dimension-content dimension”framework to form normative constraints on the system operation process from both module application and quality assurance aspects.