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Genetic algorithm based intrusion detection system for wireless body area networks

机译:基于遗传算法的无线体积网络入侵检测系统

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Driven by recent technological advances in wireless communications, wireless sensors, and low power networked systems, wireless sensor networks are emerging as a promising technology in healthcare applications. Since information transmitted in these wireless body area networks (WBAN) often consists of critical and sensitive patient health and personal information, securing these networks is central to their practical deployment in healthcare applications. The objective of this research is to design and develop an intrusion detection framework to improve security in WBAN. In this work, we propose a multi-objective genetic algorithm based intrusion detection system to provide optimal attack detection in these networks. The proposed system guarantees that only those features necessary for detecting a specific attack is used in the intrusion detection process, thereby decreasing the computational complexity.
机译:通过最近的无线通信技术进步,无线传感器和低功率网络系统的推动,无线传感器网络正在作为医疗保健应用中的有希望的技术。由于在这些无线体积网络(WBAN)中传输的信息通常由关键且敏感的患者健康和个人信息组成,因此保护这些网络是他们在医疗保健应用程序中实际部署的核心。本研究的目的是设计和开发入侵检测框架,以提高WBAN中的安全性。在这项工作中,我们提出了一种基于多目标遗传算法的入侵检测系统,在这些网络中提供最佳攻击检测。所提出的系统保证只有在入侵检测过程中使用检测特定攻击所需的特征,从而降低计算复杂性。

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