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SPECIFYING AND COMPILING HIGH LEVEL FINANCIAL FRAUD POLICIES INTO STREAMSQL

机译:指定和编制高级金融欺诈策略进入StreamSQL

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Fraud detection within financial platforms remains a challenging area in which criminals continue to thrive, breaching security mechanisms with increasingly innovative and sophisticated system attacks. Following the migration from reactive to proactive screening of transactional data to reduce an organisations fraud detection latency, fraud analysts now find themselves responsible for the maintenance of extensive fraud policy sets and their implementation as complex data stream processing procedures. This paper presents a Financial Fraud Modelling Language and policy mapping tool for high level expression and implementation of proactive fraud policies using stream processors. A key aspect of the approach is reduction of the complexity and implementation latency associated with proactive fraud policy management through abstraction of policy functionality using a conceptual level modelling language and innovative policy mapping tool. This paper focuses upon the rule based language model for high level expression of financial fraud policies and the associated compiler tool for specifying and mapping policies into StreamSQL.
机译:金融平台内的欺诈检测仍然是一个具有挑战性的地区,犯罪分子继续茁壮成长,违反安全机制,越来越创新,系统攻击。在迁移到积极筛选事务数据的主动筛选以减少组织欺诈检测延迟,欺诈分析师现在发现自己负责维护广泛的欺诈策略集及其作为复杂数据流处理过程的实现。本文介绍了一种用于高级表达式的金融欺诈建模语言和策略映射工具,使用流处理器实现主动欺诈策略。该方法的一个关键方面是通过使用概念级别建模语言和创新的策略映射工具来抽象策略功能来降低与主动欺诈策略管理相关的复杂性和实现延迟。本文重点介绍了基于规则的金融欺诈策略的高级表达式的语言模型以及用于将策略指定和映射到StreamSQL的相关编译器工具。

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