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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Patient Infusion Pattern based Access Control Schemes for Wireless Insulin Pump System
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Patient Infusion Pattern based Access Control Schemes for Wireless Insulin Pump System

机译：基于患者输液模式的无线胰岛素泵系统访问控制方案

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摘要

Wireless insulin pumps have been widely deployed in hospitals and home healthcare systems. Most of them have limited security mechanisms embedded to protect them from malicious attacks. In this paper, two attacks against insulin pump systems via wireless links are investigated: a single acute overdose with a significant amount of medication and a chronic overdose with a small amount of extra medication over a long time period. They can be launched unobtrusively and may jeopardize patients’ lives. It is very urgent to protect patients from these attacks. We propose a novel personalized patient infusion pattern based access control scheme (PIPAC) for wireless insulin pumps. This scheme employs supervised learning approaches to learn normal patient infusion patterns in terms of the dosage amount, rate, and time of infusion, which are automatically recorded in insulin pump logs. The generated regression models are used to dynamically configure a safe infusion range for abnormal infusion identification. This model includes two sub models for bolus (one type of insulin) abnormal dosage detection and basal abnormal rate detection. The proposed algorithms are evaluated with real insulin pump. The evaluation results demonstrate that our scheme is able to detect the two attacks with a very high success rate.
机译：无线胰岛素泵已广泛部署在医院和家庭医疗保健系统中。他们中的大多数人都嵌入了有限的安全机制，以保护他们免受恶意攻击。在本文中，研究了两种通过无线链路对胰岛素泵系统的攻击：一次急性过量服用大量药物，而长期过量服用少量额外药物。它们可能不引人注目地发射，并可能危及患者的生命。保护患者免受这些攻击非常迫切。我们为无线胰岛素泵提出了一种新颖的基于个性化患者输液模式的访问控制方案（PIPAC）。该方案采用监督学习方法来学习正常的患者输注方式，包括剂量，输注速率和输注时间，这些模式会自动记录在胰岛素泵记录中。生成的回归模型用于动态配置用于异常输注识别的安全输注范围。该模型包括用于推注（一种胰岛素）异常剂量检测和基础异常率检测的两个子模型。所提出的算法是用实际胰岛素泵评估的。评估结果表明，我们的方案能够以很高的成功率检测到这两次攻击。

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