Detecting the Anomaly Attacks in Industrial IoT using Hybrid Feature Selection Based Modified Convolutional Neural Network-Reference-Cited by-同舟云学术

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Detecting the Anomaly Attacks in Industrial IoT using Hybrid Feature Selection Based Modified Convolutional Neural Network

Published:2023-10-20 Issue: Volume: Page:1-7
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
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Author:

Rallapalli Sreekanth¹,Kumar Tiwari Vikas¹,D Vidya Sagar S¹,Kumar Pareek Piyush²

Affiliation:

1. Nitte Meenakshi Institute of Technology,Department of Master of Computer Applications,Bengaluru,India

2. Nitte Meenakshi Institute of Technology,Department of Artificial Intelligence and Machine Learning,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10393443.pdf?arnumber=10393443

Reference24 articles.

1. Anomaly Detection Using Deep Neural Network for IoT Architecture

2. Machine Learning for Anomaly Detection: A Systematic Review

3. Grey Wolf Optimization Parameter Control for Feature Selection in Anomaly Detection

4. A Machine Learning Approach for Anomaly Detection in Industrial Control Systems Based on Measurement Data

5. Design and Development of a Deep Learning-Based Model for Anomaly Detection in IoT Networks

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