Network Intrusion Detection based on Feature set Selection using Back-Propagation Neural Network
Supratim Paul
, Dr. R. Nagaraja , Shivakumar B R
Intrusion Detection System, Artificial Neural Network, Feature Selection
With dynamic increase of network application and electronic gadgets such as PCs, cell phones, and so on attacks and detection of intrusion became most challenging task in cybercrime detection zone. Decades ago, because of better network technology and more utility of the Internet, it became all digital in worldwide. Parallel to these enhancements, the endeavors of hackers for intruding the networks are also increased. And these attacks adversely affect the network badly. In this project for intrusion detection, an Artificial Neural Network (ANN) classification algorithm is implemented. The Network Layer-Knowledge Discovery Database data set is analyzed that contains of 41 features to study the viability of classification algorithm and intrusion attack detection is made by using Back-Propagation method to achieve more accuracy. Artificial neural network model gives the best number of features of 22 attributes need for detecting the intrusion and which is further categorized into more and less significant attributes. Hence, improves the accuracy and saving of resources is done.
"Network Intrusion Detection based on Feature set Selection using Back-Propagation Neural Network", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 11, page no.106 - 114, November-2018, Available :https://ijsdr.org/papers/IJSDR1811019.pdf
Volume 3
Issue 11,
November-2018
Pages : 106 - 114
Paper Reg. ID: IJSDR_180654
Published Paper Id: IJSDR1811019
Downloads: 000347183
Research Area: Engineering
Country: Bengaluru, Karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
