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Detection of Malicious Data using hybrid of Classification and Clustering Algorithms under Data Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 104 - Number 11 |
| Year of Publication: 2014 |
| Authors: Milan Jain, Bikram Pal |
10.5120/18244-9193
|
Milan Jain, Bikram Pal . Detection of Malicious Data using hybrid of Classification and Clustering Algorithms under Data Mining. International Journal of Computer Applications. 104, 11 ( October 2014), 4-7. DOI=10.5120/18244-9193
Abstract
In today era modern infrastructures and technologies are more prone to various types of accesses. A method that is commonly used for launching these types of attack is popularly known as malware i. e. viruses, Trojan horses and worms, which, when propagate can cause a great damage to commercial companies, private users and governments. The another reason that enhance malware to infect and spread very rapidly is high-speed Internet connections as it has become more popular now a days, therefore it is very important to eradicate and detect new (benign) malware in a prompt manner. Hence in this work, proposing three data mining algorithms to produce new classifiers with separate features: RIPPER, Naïve Bayes and a Multi Classifier system along with hybrid of clustering techniques and the comparison between these methods to predict which provides better results.
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