What is it about?
Many Internet of Things (IoT) devices are susceptible to cyber-attacks. Attackers can exploit these flaws using the internet and remote access. An efficient Intelligent threat detection framework is proposed for IoT networks. This paper considers four key layout ideas while building a deep learning-based intelligent threat detection system at the edge of the IoT.
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Why is it important?
Raw IoT traffic data is pre-processed with spark. Deep Vectorized Convolution Neural Network (VCNN) and Stacked Long Short Term Memory Network build the classification model (SLSTM). VCNN is used for extracting meaningful features of network traffic data, and SLSTM is used for classification and prevents the DL model from overfitting.
Perspectives
Writing this article explores the significance of addressing security vulnerabilities in IoT devices. It proposes a hybrid deep learning approach as a potential solution to enhance threat detection capabilities in IoT networks.
D Santhadevi
Read the Original
This page is a summary of: HSDL-based intelligent threat detection framework for IoT network, Journal of Intelligent & Fuzzy Systems Applications in Engineering and Technology, July 2023, IOS Press,
DOI: 10.3233/jifs-223246.
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