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Effective Features for Detection of Remote Access Trojans

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dc.contributor.author Yin, Khin Swe
dc.contributor.author Khine, May Aye
dc.date.accessioned 2019-07-12T03:30:30Z
dc.date.available 2019-07-12T03:30:30Z
dc.date.issued 2017-02-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/795
dc.description.abstract As companies in every industry sector around the globe have lost, stolen or leaked their sensitive data to the outside world every year, the security of confidential information is increasingly important. Remote Access Trojans (RATs) are used to invade a victim’s PC through targeted attacks. In the previous works features for detection of RATs were selected by the author who may be an expert in the related domain, and any feature selection method was not used. In this paper one of the feature selection methods, Information Gain is applied for evaluating and ranking features. It aims not only to reduce costs and resources for building detection system of remote Access Trojan but also to add the advantages of using feature selection method and propose new features while maintaining high accuracy. Our approach achieves 99% accuracy together with the FNR of 0.091 by Decision Trees algorithm, and this experimental result shows that our proposed features are effective to detection system of RATs. en_US
dc.language.iso en en_US
dc.publisher Fifteenth International Conference on Computer Applications(ICCA 2017) en_US
dc.title Effective Features for Detection of Remote Access Trojans en_US
dc.type Article en_US

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