Survey on Intrusions Detection System using Deep learning in IoT Environment

B. R, S. Deepajothi, Prabaharan G, Daniya T, P. Karthikeyan, V. S
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引用次数: 4

Abstract

The enormous development of information sent through the IoT devices to end-user devices has expanded the significance of creating intrusion detection systems. Intrusion detection system plays a vital role in the smart home, smart city, agriculture, and business organizations. The intruder crate attack and send the data through the IoT sensor device to attack the IoT environment. There is numerous deep learning model is developed and deployed in the IoT environment to detect the intrusion's activity in the IoT environment. This survey paper explores the deep supervised learning model, deep unsupervised learning model, and data set used in the IoT environment for the intrusions detection system. Finally, the open research problem in the intrusion detection system in the IoT environment is presented.
物联网环境下基于深度学习的入侵检测系统研究
通过物联网设备发送到最终用户设备的信息的巨大发展扩大了创建入侵检测系统的重要性。入侵检测系统在智能家居、智慧城市、农业和商业组织中发挥着至关重要的作用。入侵者发起攻击并通过物联网传感器设备发送数据来攻击物联网环境。在物联网环境中开发和部署了许多深度学习模型来检测物联网环境中的入侵活动。本文探讨了入侵检测系统中物联网环境中使用的深度监督学习模型、深度无监督学习模型和数据集。最后,提出了物联网环境下入侵检测系统的开放性研究问题。
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