@inproceedings{4b4cb07b7f1f4fbe8867f2abc9188902,
title = "The algorithm of malicious code detection based on data mining",
abstract = "Traditional technology of malicious code detection has low accuracy and it has insufficient detection capability for new variants. In terms of malicious code detection technology which is based on the data mining, its indicators are not accurate enough, and its classification detection efficiency is relatively low. This paper proposed the information gain ratio indicator based on the N-gram to choose signature, this indicator can accurately reflect the detection weight of the signature, and helped by C4.5 decision tree to elevate the algorithm of classification detection.",
keywords = "Data Mining, Decision Tree, Information Gain, Malicious Code",
author = "Yubo Yang and Yang Zhao and Xiabi Liu",
note = "Publisher Copyright: {\textcopyright} 2017 Author(s).; 2017 International Conference on Green Energy and Sustainable Development, GESD 2017 ; Conference date: 27-05-2017 Through 28-05-2017",
year = "2017",
month = jul,
day = "31",
doi = "10.1063/1.4992960",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Jun Xiao and Lin Liu and Jianfeng Ke",
booktitle = "Green Energy and Sustainable Development I",
address = "United States",
}