NDLI: Review on speedup and accurate intrusion detection system by using MSPSO and data mining technology

Content Provider	IEEE Xplore Digital Library
Author	Umak, M.R. Raghuwanshi, K.S. Mishra, R.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci. & Eng., OCT, Raisen, India (Raghuwanshi, K.S.; Mishra, R.) \|\| Dept. of Comput. Sci. & Eng., OCT, Akola, India (Umak, M.R.)
Abstract	Intrusion detection is the act of detecting unwanted traffic on a network or a device. An IDS can be a piece of installed software or a physical appliance that monitors network traffic in order to detect unwanted activity and events such as illegal and malicious traffic, traffic that violates security policy, and traffic that violates acceptable use policies. However, Intrusion detection systems face a number of challenges. One of the important challenges is that, the input data to be classified is in a high dimension feature space. In this paper, we are trying to present MSPSO-DT intrusion detection system. Where, Multi Swam Particle Swarm Optimization (MSPSO) is used as a feature selection algorithm to maximize the C4.5 Decision Tree classifier detection accuracy and minimize the timing speed. To evaluate the performance of the presented MSPSO-DT IDS we are trying to use several experiments on NSL-KDD benchmarked network intrusion detection dataset.
Sponsorship	IEEE Madhya Pradesh Subsect.
Starting Page	1
Ending Page	6
File Size	630686
Page Count	6
File Format	PDF
ISBN	9781479925254
e-ISBN	9781479925261
DOI	10.1109/SCEECS.2014.6804504
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-01
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Feature Selection Decision Tree Intrusion detection Ports (Computers) Network Security Multi Swam Particle Swarm Optimization Classification algorithms Servers Data mining Decision trees Intrusion Detection System
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A new data mining based network Intrusion Detection model

An analysis of supervised tree based classifiers for intrusion detection system

A Feature Selection Algorithm to Intrusion Detection Based on Cloud Model and Multi-Objective Particle Swarm Optimization

Optimizing SMOTE by Metaheuristics with Neural Network and Decision Tree

Network intrusion detection system using J48 Decision Tree

Machine Learning Techniques for Feature Reduction in Intrusion Detection Systems: A Comparison

Network intrusion detection using feature selection and Decision tree classifier

The Architecture of Host-based Intrusion Detection Model Generation System for the Frequency Per System Call

A hybrid network intrusion detection using darwinian particle swarm optimization and stacked autoencoder hoeffding tree

Review on speedup and accurate intrusion detection system by using MSPSO and data mining technology

Similar Documents

A new data mining based network Intrusion Detection model

An analysis of supervised tree based classifiers for intrusion detection system

A Feature Selection Algorithm to Intrusion Detection Based on Cloud Model and Multi-Objective Particle Swarm Optimization

Optimizing SMOTE by Metaheuristics with Neural Network and Decision Tree

Network intrusion detection system using J48 Decision Tree

Machine Learning Techniques for Feature Reduction in Intrusion Detection Systems: A Comparison

Network intrusion detection using feature selection and Decision tree classifier

The Architecture of Host-based Intrusion Detection Model Generation System for the Frequency Per System Call

A hybrid network intrusion detection using darwinian particle swarm optimization and stacked autoencoder hoeffding tree

Review on speedup and accurate intrusion detection system by using MSPSO and data mining technology