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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人体局域网入侵检测系统

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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:在无线通信,无线传感器和低功耗联网系统的最新技术进步的推动下,无线传感器网络正在成为医疗保健应用中的一项有前途的技术。由于在这些无线人体局域网(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,因此保护这些网络对其在医疗保健应用中的实际部署至关重要。这项研究的目的是设计和开发入侵检测框架,以提高WBAN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,以在这些网络中提供最佳的攻击检测。提出的系统保证在入侵检测过程中仅使用检测特定攻击所必需的那些功能,从而降低了计算复杂性。

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