scholarly journals Self Organizing Maps to Build Intrusion Detection System

2010 ◽  
Vol 1 (8) ◽  
pp. 1-4 ◽  
Author(s):  
V. K. Pachghare ◽  
Vivek A. Patole ◽  
Dr. Parag Kulkarni
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Self Organizing Maps ◽  
Self Organizing

A Self Organizing Map Intrusion Detection System for RPL Protocol Attacks

2019 ◽  
Vol 11 (1) ◽  
pp. 30-43 ◽  
Author(s):  
Elie Kfoury ◽  
Julien Saab ◽  
Paul Younes ◽  
Roger Achkar
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Early Stage ◽  
Sensor Data ◽  
Self Organizing Map ◽  
Lossy Networks ◽  
Mesh Topology ◽  
Som Neural Network ◽  
Self Organizing

Routing over low power and lossy networks (RPL) is a standardized routing protocol for constrained Wireless Sensor Network (WSN) environments. The main node's constraints include processing capability, power, memory, and energy. RPL protocol describes how WSN nodes create a mesh topology, enabling them to route sensor data. Unfortunately, various attacks exist on the RPL protocol that can disrupt the topology and consume nodes' energy. In this article, the authors propose an intrusion detection system (IDS) based on self-organizing map (SOM) neural network to cluster the WSN routing attacks, and hence notify the system administrator at an early stage, reducing the risk of interrupting the network and consuming nodes' power. Results showed that the proposed SOM architecture is able to cluster routing packets into three different types of attacks, as well as clean data.

scholarly journals Intrusion Detection System Using Back Propagation Algorithm and Compare its Performance with Self Organizing Map

2016 ◽  
Vol 1 ◽  
pp. 127 ◽  
Author(s):  
Subarna Shakya ◽  
Bisho Raj Kaphle
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Back Propagation ◽  
Attack Behavior ◽  
Main Function ◽  
Self Organizing Map ◽  
Back Propagation Algorithm ◽  
Network Intrusion ◽  
Self Organizing

<p>In recent years, internet and computers have been utilized by many people all over the world in several fields. On the other hand, network intrusion and information safety problems are ramifications of using internet. In this thesis it propose a new learning methodology towards developing a novel intrusion detection system (IDS) by back propagation neural networks (BPN) and self organizing map (SOM) and compare the performance between them. The main function of Intrusion Detection System is to protect the resources from threats. It analyzes and predicts the behaviors of users, and then these behaviors will be considered an attack or a normal behavior. The proposed method can significantly reduce the training time required. Additionally, the training results are good. It provides a powerful tool to help supervisors and unsupervisors analyze, model and understand the complex attack behavior of electronic crime.</p><p><em>Journal of Advanced College of Engineering and Management, Vol. 1, 2015</em>, pp. 127-138</p>

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