A Novel Hybrid Deep Learning Framework for Intrusion Detection Systems in WSN-IoT Networks

IF 2 4区计算机科学 Q2 Computer Science

Intelligent Automation and Soft Computing Pub Date : 2022-01-01 DOI:10.32604/iasc.2022.022259

M. Maheswari, R. A. Karthika

引用次数: 5

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一种用于WSN-IoT网络入侵检测系统的混合深度学习框架

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Intelligent Automation and Soft Computing 工程技术-计算机：人工智能

CiteScore

3.50

自引率

10.00%

发文量

429

审稿时长

10.8 months

期刊介绍： An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing. The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing. It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.