Journal on Communications ›› 2017, Vol. 38 ›› Issue (5): 190-198.doi: 10.11959/j.issn.1000-436x.2017095

• Academic communication • Previous Articles     Next Articles

Android malware detection based on APK signature information feedback

Xin-yu LIU,Jian WENG,Yue ZHANG,Bing-wen FENG,Jia-si WENG   

  1. College of Information Science and Technology,Jinan University,Guangzhou 510632,China
  • Revised:2017-03-09 Online:2017-05-01 Published:2017-05-28
  • Supported by:
    The National Natural Science Foundation of China(61133014);The National Natural Science Foundation of China(61272413);The National Natural Science Foundation of China(61373158);The National Natural Science Foundation of China(61472165);Key Program for Guangdong Province Applied Science and Technology R&D Special Funds(2016B010124009)

Abstract:

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%.

Key words: false positive rate, malicious application, heuristic learning, effectiveness, detection rate

CLC Number: 

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