Open AccessIntrusion Detection System using SMIFS and Multi class Multi layer Perceptron
Author(s) -
V. Maheshwar Reddy,
I. Ravi Prakash Reddy,
K. Adi Narayana Reddy
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i8982.078919
Subject(s) - computer science , feature selection , artificial intelligence , data mining , perceptron , class (philosophy) , feature extraction , mutual information , intrusion detection system , pattern recognition (psychology) , machine learning , feature (linguistics) , multilayer perceptron , curse of dimensionality , overhead (engineering) , data set , artificial neural network , philosophy , linguistics , operating system
As the new technologies are emerging, data is getting generated in larger volumes high dimensions. The high dimensionality of data may rise to great challenge while classification. The presence of redundant features and noisy data degrades the performance of the model. So, it is necessary to extract the relevant features from given data set. Feature extraction is an important step in many machine learning algorithms. Many researchers have been attempted to extract the features. Among these different feature extraction methods, mutual information is widely used feature selection method because of its good quality of quantifying dependency among the features in classification problems. To cope with this issue, in this paper we proposed simplified mutual information based feature selection with less computational overhead. The selected feature subset is experimented with multilayered perceptron on KDD CUP 99 data set with 2- class classification, 5-class classification and 4-class classification. The accuracy is of these models almost similar with less number of features.