An Accurate Method for Deteetion of Cyber Attaeks
| dc.category | Journal Article | |
| dc.contributor.author | Padmavathi, G | |
| dc.contributor.author | Uma, M | |
| dc.date.accessioned | 2017-04-18T19:32:48Z | |
| dc.date.available | 2017-04-18T19:32:48Z | |
| dc.date.issued | 2013 | |
| dc.department | Information Technology | en_US |
| dc.description.abstract | Due to the rapid growth of wireless local area networks in day-to-day applications detection of cyber attacks have been increasing. In 2012, a survey stated that an organization experiences with an average of 102 attacks every week, whereas 72 attacks and 50 attacks were detected during 2011 and 2010, approxmiately 42% of attacks have increased in a year. In this paper, the dimensionality reduction techniques are used to detect the cyber attacks. The objective of this research work is to extract the meaningful class labels in the data set using linear dimensionality reduction techniques like Principal Components Analysis (PCA), Independent Component Analysis (ICA) and Linear Discriminant analysis (LDA). The experimental study shows that PCA performs better than LDA and ICA. To improve the obtained results the PCA is combined with SVM, where an accuracy rate increases in the detection of cyber attacks. | en_US |
| dc.identifier.uri | https://ir.avinuty.ac.in/handle/avu/3243 | |
| dc.lang | English | en_US |
| dc.publisher.name | Australian Journal of Basic and Applied Sciences | en_US |
| dc.publisher.type | International | en_US |
| dc.title | An Accurate Method for Deteetion of Cyber Attaeks | en_US |
Files
Original bundle
1 - 1 of 1