Indian Journal of Automation and Artificial Intelligence

The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


Background/Objectives: To design the best and worst solution and also to minimise false alarm rate and maximize the detection rate by using AJO

Methods/Statistical analysis: The Adaptive Jaya Optimization (AJO) technique is used to select best features among 41 features.

Findings: The intrusion detection work focuses on feature selection, because few of the features are inappropriate and additional which results prolonged detection procedure and diminishes the performance of an intrusion detection system (IDS). With AJO technique best 17 features were selected to have best accuracy.

Application: In this study the NSL-KDD data set is analysed and applied Adaptive Jaya Technique for selecting best features to minimize low false alarm rate & maximize detection rate.


Keywords

Intrusion Detection System, NSL-KDD Dataset, Feature Selection, Adaptive Jaya Optimization.
User
Notifications