The Algorithm of Malicious Code Detection Based on Data Mining

被引：1

作者：

Yang, Yubo ^{[1
]}

Zhao, Yang ^{[1
]}

Liu, Xiabi ^{[2
]}

机构：

[1] Beijing E Hualu Informat Technol CO LTD, Beijing 100043, Peoples R China

[2] Beijing Inst Technol, Beijing 100081, Peoples R China

来源：

GREEN ENERGY AND SUSTAINABLE DEVELOPMENT I | 2017年 / 1864卷

关键词：

Malicious Code; Data Mining; Information Gain; Decision Tree;

D O I：

10.1063/1.4992960

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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.

引用

页数：5

共 50 条

[1] Malicious Code Forensics based on Data Mining
Li, Xiaohua
Dong, Xiaomei
Wang, Yulong
2013 10TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD), 2013, : 978 - 983
[2] Malicious VBScript Detection Algorithm Based on Data-Mining Techniques
Wael, Doaa
Shosha, Ahmed
Sayed, Samir G.
2017 INTL CONF ON ADVANCED CONTROL CIRCUITS SYSTEMS (ACCS) SYSTEMS & 2017 INTL CONF ON NEW PARADIGMS IN ELECTRONICS & INFORMATION TECHNOLOGY (PEIT), 2017, : 112 - 116
[3] A Malicious Mining Code Detection Method Based on Multi-Features Fusion
Li, Shudong
Jiang, Laiyuan
Zhang, Qianqing
Wang, Zhen
Tian, Zhihong
Guizani, Mohsen
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2023, 10 (05): : 2731 - 2739
[4] Malicious mining code detection based on ensemble learning in cloud computing environment
Li, Shudong
Li, Yuan
Han, Weihong
Du, Xiaojiang
Guizani, Mohsen
Tian, Zhihong
SIMULATION MODELLING PRACTICE AND THEORY, 2021, 113
[5] An Android Malicious Code Detection Method Based on Improved DCA Algorithm
Wang, Chundong
Li, Zhiyuan
Gong, Liangyi
Mo, Xiuliang
Yang, Hong
Zhao, Yi
ENTROPY, 2017, 19 (02):
[6] Review of malicious code detection in data mining applications: challenges, algorithms, and future direction
Razaque, Abdul
Bektemyssova, Gulnara
Yoo, Joon
Hariri, Salim
Khan, Meer Jaro
Nalgozhina, Nurgul
Hwang, Jaeryong
Khan, M. Ajmal
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2025, 28 (03):
[7] Malicious Code Detection Technology Based on A3C Algorithm
Xue, Yi
Shu, Hui
Bu, Wenjuan
Qu, Wu
PROCEEDINGS OF 2020 IEEE 11TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2020), 2020, : 116 - 120
[8] Malicious code detection based on CNNs and multi-objective algorithm
Cui, Zhihua
Du, Lei
Wang, Penghong
Cai, Xingjuan
Zhang, Wensheng
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2019, 129 : 50 - 58
[9] Malicious Code Detection Based on Code Semantic Features
Zhang, Yu
Li, Binglong
IEEE ACCESS, 2020, 8 : 176728 - 176737
[10] COMPUTER MALICIOUS CODE SIGNAL DETECTION BASED ON BIG DATA TECHNOLOGY
Liu, Xiaoteng
SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2023, 24 (03): : 521 - 530

← 1 2 3 4 5 →