Open AccessA Review on Intrusion Detection System Based on Various Learning Techniques
Author(s) -
Shiladitya Raj,
Megha Jain,
Megha Kamble
Publication year - 2021
Publication title -
indian journal of artificial intelligence and neural networking (ijainn)
Language(s) - English
Resource type - Journals
ISSN - 2582-7626
DOI - 10.35940/ijainn.b1013.041221
Subject(s) - intrusion detection system , computer science , the internet , computer security , host (biology) , network security , deep learning , state (computer science) , artificial intelligence , world wide web , ecology , algorithm , biology
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.