A Review on Intrusion Detection System Based on Various Learning Techniques 
Shiladitya Raj1, Megha Jain2, Megha Kamble3
1Shiladitya Raj, Student, Department of computer science and Engineering, Lakshmi Narain College of Technology Excellence Bhopal, India.
2Megha Jain, Assistant professor, Department of computer science and Engineering, Lakshmi Narain College of Technology Excellence Bhopal, India.
3Megha kamble, Assistant professor, Department of computer science and Engineering, Lakshmi Narain College of Technology Excellence Bhopal, India.
Manuscript received on 27 March 2021 | Revised Manuscript received on 10 April 2021 | Manuscript Accepted on 15 April 2021 | Manuscript published on 30 April 2021 | PP: 36-42 | Volume-1 Issue-2, April 2021 | Retrieval Number: 100.1/ijainn.B1013021221 | DOI: 10.54105/ijainn.B1013.041221
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this world of the Internet, security plays an important role as Internet users grow rapidly. Security in the network is one of the modern periods’ main issues. In the last decade, the exponential growth and massive use of the Internet have enabled system security vulnerabilities a critical aspect. Intrusion detection system to track unauthorized access as well as exceptional attacks through secured networks. Several experiments on the IDS have been carried out in recent years. And to know the current state of machine learning approaches to address the issue of intrusion detection. IDS is commonly used for the detection and recognition of cyberattacks at the network and host stage, in a timely and automatic manner. This research assesses the creation of a deep neural network (DNN), a form of deep learning model as well as ELM to detect unpredictable and unpredictable cyber-attacks.
Keywords: Intrusion Detection System, Deep Learning, Extreme Learning, Machine, Deep Belief Network (DBN).
Scope of the Article: Supervised Learning