Intrusion-Miner: A Hybrid Classifier for Intrusion Detection using Data Mining
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 4
Abstract
With the rapid growth and usage of internet, number of network attacks have increase dramatically within the past few years. The problem facing in nowadays is to observe these attacks efficiently for security concerns because of the value of data. Consequently, it is important to monitor and handle these attacks and intrusion detection system (IDS) has potentially diagnostic ability to handle these attacks to secure the network. Numerous intrusion detection approaches are presented but the main hindrance is their performance which can be improved by increasing detection rate as well as decreasing false positive rates. Optimizing the performance of IDS is very serious issue and challenging fact that gets more attention from the research community. In this paper, we proposed a hybrid classification approach ‘Intrusion-Miner’ with the help of two classifier algorithm for network anomaly detection to get optimum result and make it possible to detect network attacks. Thus, principal component analysis (PCA) and Fisher Discriminant Ratio (FDR) have been implemented for the feature selection and noise removal. This hybrid approach is compared with J48, Bayesnet, JRip, SMO, IBK and evaluate the performance using KDD99 dataset. Experimental result revealed that the precision of the proposed approach is measured as 96.1 % with low false positive and high false negative rate as compare to other state-of-the-art algorithm. The simulation result evaluation shows that perceptible progress and real-time intrusion detection can be attained as we apply the suggested models to identify diverse kinds of network attacks.
Authors and Affiliations
Samra Zafar, Muhammad Kamran, Xiaopeng Hu
Keywords
Related Articles
- EP ID EP551404
- DOI 10.14569/IJACSA.2019.0100440
- Views 71
- Downloads 0
Enhanced K-mean Using Evolutionary Algorithms for Melanoma Detection and Segmentation in Skin Images
Nowadays, Melanoma has become one of the most significant public health concerns. Malignant Melanoma (MM) is considered the most rapidly spreading type of skin cancer. In this paper, we have built models for detection, s...
MVC Frameworks Modernization Approach
The use of web development frameworks has grown significantly, specially the Model-View-Controller (MVC) based frameworks. The ability to immigrate web applications between different frameworks available becomes more and...
Impact of External Disturbance and Discontinuous Input on the Redundant Manipulator Robot Behaviour using the Linear Parameter Varying Modelling Approach
This paper is concerned with the synthesis of dynamic model of the redundant manipulator robot based on Linear Parameter Varying approach. To evaluate its behavior and in presence of external disturbance several motions...
Simulation of Performance Execution Procedure to Improve Seamless Vertical Handover in Heterogeneous Networks
One challenge of wireless networks integration is the ubiquitous wireless access abilities which provide the seamless handover for any moving communication device between different types of technologies (3GPP and non-3GP...
Development of Purchasing Module for Agriculture E-Commerce using Dynamic System Development Model
Trading model has been changing since the vast implementation of Information and Communication Technology in every sector. This model is known as e-Commerce. Unlikely, there is still limited company which specifically tr...