REVIEW TECHNIQUE FOR INTRUSION DETECTION MODEL USING RECURRENT NEURAL NETWORKS

Author Name: 1. Avani Bhoyar 2. Dr. Vinod Patel

Volume/Issue: 02/02

Country: India

DOI NO.: 08.2020-25662434 DOI Link: https://www.doi-ds.org/doilink/07.2021-88742435/UIJIR

Affiliation:

Lakshmi Narain College of Technology, Bhopal, Madhya Pradesh, India (affiliated by AICTE, RGPV)

ABSTRACT

Intrusion detection system (IDS) arrangements with the problematic of fault detection, less accurateness, delays and estimate of attack types. Thus the Review Technique work recommend a data mining based IDS that include the methods that supports to appreciate the network behaviour and predict the attack type precisely after the network traces. IDS are the network monitoring methods that scan the network to recognize the behavioural variations in network. The main purpose of IDS system is to classify the attack situations happened in network and to recognize the nature of attack organised in the network.

Key words: IDS, Recurrent Neural Networks

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