Abstract This paper aims to secure money transactions due to money laundering crimes. It presents a Secure Intelligent Framework for Anti-Money Laundering (SIFAML). This framework is new and includes two main processes. In addition, it supports several modules. The first process is the monitoring process for detecting possible ML. The second process is a STRIPS-based planning process that targets strengthening the belief in the potential problems detected in the monitoring process. In addition, STRIPS is a hierarchical planning technique that makes utilization of the means-ends tactic, by finding the goal in the root of the hierarchical. It searches gradually for the plan services that can diminish the distinction between the current state and the goal. An important feature of SIFAML is the integration of the planner and the OWL-'s reasoner. This means that the reasoner might do the entire planner’s interactions with a particular state. In addition, SIFAML contains several supporting modules for data gathering and mediation, link analysis, and risk scoring. To present the applicability of SIFAML, it has been discussed using different instances. This work provides an analytical study and a comparison between the performance and capabilities of SIFAML and other related works are given and the concluding remarks are discussed. The proposed framework improves the discovery of ML and reduces false-positive alarms. It moves anti-money laundering frameworks to make use of an intelligent formalism by using ontology and STRIPS-based planning. Finally, this work introduces SIFAML as a novel ontology-based and plan-based system for AML frameworks.

中文翻译：

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一种反洗钱的智能安全框架

摘要本文旨在保护因洗钱犯罪引起的货币交易。它提出了一个安全的反洗钱智能框架（SIFAML）。该框架是新的，包括两个主要过程。另外，它支持几个模块。第一个过程是用于检测可能的ML的监视过程。第二个过程是基于STRIPS的计划过程，旨在加强对监视过程中发现的潜在问题的信念。另外，STRIPS是一种分层计划技术，通过在分层结构的根源中找到目标，从而利用了均值末端策略。它逐步搜索可以减少当前状态和目标之间区别的计划服务。SIFAML的一个重要功能是计划程序和OWL-推理机的集成。这意味着推理者可能会与特定状态进行整个计划者的交互。此外，SIFAML包含几个支持模块，用于数据收集和中介，链接分析以及风险评分。为了展示SIFAML的适用性，已使用不同的实例对其进行了讨论。这项工作提供了分析研究，并比较了SIFAML和其他相关工作的性能和功能，并讨论了结论。所提出的框架改进了ML的发现并减少了假阳性警报。它通过使用本体和基于STRIPS的计划来移动反洗钱框架以利用智能形式主义。最后，这项工作介绍了SIFAML，这是一种针对AML框架的新颖的基于本体和基于计划的系统。