APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System-Reference-Cited by-同舟云学术

APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System

Published:2023 Issue: Volume:11 Page:74000-74020
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Javed Safdar Hussain¹,Ahmad Maaz Bin¹^ORCID,Asif Muhammad²^ORCID,Akram Waseem²,Mahmood Khalid³^ORCID,Das Ashok Kumar⁴^ORCID,Shetty Sachin⁵^ORCID

Affiliation:

1. College of Computing and Information Sciences, Karachi Institute of Economics and Technology (KIET), Karachi, Pakistan

2. Department of Computer Science, Lahore Garrison University, Lahore, Pakistan

3. Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, Douliu, Taiwan

4. Center for Security, Theory and Algorithmic Research, International Institute of Information Technology at Hyderabad, Hyderabad, India

5. Department of Modeling, Simulation and Visualization Engineering, Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Suffolk, VA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10171354.pdf?arnumber=10171354

Reference59 articles.

1. 1D CNN based network intrusion detection with normalization on imbalanced data

2. A Novel Two-Stage Deep Learning Model for Network Intrusion Detection: LSTM-AE

3. Detection of advanced persistent threat using machine-learning correlation analysis

4. NIDS-CNNLSTM: Network Intrusion Detection Classification Model Based on Deep Learning

5. An Evaluation of Machine Learning Algorithms To Detect Attacks in Scada Network

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