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Data Security Platform Model in Networked Medical IT Systems based on Statistical Classifiers and ANN

机译:基于统计分类器和ANN的网络医疗IT系统数据安全平台模型

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The paper presents the results of research on improving the security of medical information systems. It begins with a presentation of the specific features of such systems in terms of functionality and potential risks. It was assumed that the features distinguishing medical systems from other information systems are: patient orientation, confidentiality of the information processed, state interference in the functioning of medical entities and the need to ensure maximum availability of system resources. The last requirement results from treating medical IT systems as elements of critical infrastructure, for which business continuity is one of the key features. The work focused on limiting the systems’ sensitivity to cyber-attacks limiting their availability. A software and hardware platform dedicated for attack detection is presented. The system uses parallel processing and artificial intelligence and is distinguished by several alternative detection methods, the use of expert system to make decisions about protection measures and the ability to independently identify unknown attacks. Paper ends with an evaluation of prototype testing results and directing further work in this area. The work is address to people involved in the operation of medical information systems.
机译:本文提出了提高医疗信息系统安全的研究结果。它开始于在功能性和潜在风险方面的这种系统的特定特征的呈现。假设从其他信息系统区分医疗系统的特征是:患者取向,信息处理的机密性,医学实体功能的状态干扰以及确保系统资源的最大可用性的需要。最后的要求是将医疗IT系统视为关键基础架构的元素,其中业务连续性是关键特征之一。这项工作侧重于将系统对网络攻击的敏感性限制限制了它们的可用性。提出了专用于攻击检测的软件和硬件平台。该系统使用并行处理和人工智能,并通过几种替代检测方法,使用专家系统做出决定保护措施和独立识别未知攻击的能力。纸张结束,评估原型测试结果并指导该地区的进一步工作。这项工作是参与医疗信息系统运作的人的地址。

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