IoT Intrusion Detection Using Two-Tier-Convolutional Deep-Learning Model-Reference-Cited by-同舟云学术

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IoT Intrusion Detection Using Two-Tier-Convolutional Deep-Learning Model

Published:2023-06-23 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on IoT, Communication and Automation Technology (ICICAT)
language:
Short-container-title:

Author:

E Geo Francis¹,Sheeja S²,F Antony John E.³

Affiliation:

1. Karpagam Academy of Higher Education,Dept. of Computer Science,Coimbatore,Tamil Nadu,India

2. Dept. of Computer Science, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India

3. St. Thomas College (Autonomous),Dept. of Mathematics,Thrissur,Kerala,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10263612/10263593/10263655.pdf?arnumber=10263655

Reference19 articles.

1. Metaheuristic Algorithms-based Feature Selection Approach for Intrusion Detection

2. A novel metaheuristics with deep learning enabled intrusion detection system for secured smart environment

3. Intrusion Detection System for Internet of Things Based on Temporal Convolution Neural Network and Efficient Feature Engineering

4. Advanced Feature Extraction and Selection Approach Using Deep Learning and Aquila Optimizer for IoT Intrusion Detection System

5. An Effective Feature Selection Model Using Hybrid Metaheuristic Algorithms for IoT Intrusion Detection

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