Improving the detection accuracy of unknown malware by partitioning the executables in groups
Cryptography and Security
2018-09-18 v1
Abstract
Detection of unknown malware with high accuracy is always a challenging task. Therefore, in this paper, we study the classification of unknown malware by two methods. In the first/regular method, similar to other authors [17][16][20] approaches we select the features by taking all dataset in one group and in the second method, we select the features by partitioning the dataset in the range of file 5 KB size. We find that the second method to detect the malware with ~8.7% more accurate than the first/regular method.
Keywords
Cite
@article{arxiv.1606.06909,
title = {Improving the detection accuracy of unknown malware by partitioning the executables in groups},
author = {Ashu Sharma and Sanjay K. Sahay and Abhishek Kumar},
journal= {arXiv preprint arXiv:1606.06909},
year = {2018}
}
Comments
Proceedings 9th ICACCT, 2015, 8 Pages, 7 Figures