Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering

A Static Malicious Javascript Detection Using SVM

Authors
Wei-Hong WANG, Yin-Jun LV, Hui-Bing CHEN, Zhao-Lin FANG
Corresponding Author
Wei-Hong WANG
Available Online March 2013.
DOI
https://doi.org/10.2991/iccsee.2013.56How to use a DOI?
Keywords
SVM, static detection, malicious script detection
Abstract
Malicious script,such as JavaScript, is one of the primary threats of the network security. JavaScript is not only a browser scripting language that allows developers to create sophisticated client-side interfaces for web applications, but also used to carry out attacks taht used to steal users' credentials and lure users into providing sensitive information to unauthorized parties. We propose a static malicious JavaScript detection techniques based on SVM(Support Vector Machine). Our approach combines static detection with machine learning technique, to analyze and extract malicious script features,and use the machine learning technology,SVM, to classify the scripts.This technique has the characteristics of high detection rate,low false positive rate and the detection of unknown attacks. Applied to experiments on the prepared data set, we achieved excellent detection performance.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
978-90-78677-61-1
DOI
https://doi.org/10.2991/iccsee.2013.56How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wei-Hong WANG
AU  - Yin-Jun LV
AU  - Hui-Bing CHEN
AU  - Zhao-Lin FANG
PY  - 2013/03
DA  - 2013/03
TI  - A Static Malicious Javascript Detection Using SVM
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iccsee.2013.56
DO  - https://doi.org/10.2991/iccsee.2013.56
ID  - WANG2013/03
ER  -