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Dynamic Detection of Malicious Code on Android Based on Improved Multi-feature Gaussian Kernel

  • Qing Yu
  • Xixi Luo
  • Zuohua WangEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1075)

Abstract

In recent years, with the increasing demand for mobile Internet, smartphones represented by the Android system begin to play an increasingly important role in people’s daily life. Due to the payment and social functions of smartphones, users’ property safety and personal privacy are increasingly threatened by malicious mobile apps. Lured by great interests, malicious applications began to spread in the mobile platform, malicious code is escalating, Android-side security is facing great threats. Therefore, it is very important to study the detection of malicious code in Android. This paper studies and analyzes the status of Android malicious code detection. On the basis of dynamic detection, this paper presents a dynamic detection algorithm of multi-feature IGK. The algorithm optimizes feature selection and Gaussian kernel function and applies the improved algorithm to multi-feature training to improve the detection accuracy of malicious code. We track application system calls and system service calls while the system is running, extract features from system call sequences and system service calls. Then we use the improved weighted information gain method to select the features. Finally, in view of the deficiencies of the traditional Gaussian kernel function in recognition rate and processing time, an improved Gaussian kernel function is proposed for machine learning. We evaluated our approach with 800 benign applications and 1200 malicious applications. The experimental results show that by the above two improvements, the highest detection rate is 97.5%, better than the existing methods.

Keywords

Android Dynamic analysis System call System service Gaussian kernel 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Tianjin Key Laboratory of Intelligence Computing and Network SecurityTianjin University of TechnologyTianjinChina
  2. 2.China Everbright Bank Co., Ltd.TianjinChina

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