Android malware detection based on APK signature information feedback

Android malware detection based on APK signature information feedback

A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,fro...

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Bibliographic Details
Main Authors: Xin-yu LIU, Jian WENG, Yue ZHANG, Bing-wen FENG, Jia-si WENG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2017-05-01
Series:Tongxin xuebao
Subjects:
false positive rate
malicious application
heuristic learning
effectiveness
detection rate
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017095/
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Summary:A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,from which achieved the purpose of more accurate detection of malicious software.SigFeedback detection algorithm enjoyed the advantage of the high detection rate and low false positive rate.Finally the experiment show that the SigFeedback algorithm has high efficiency,making the rate of false positive from 13% down to 3%.
ISSN:1000-436X

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