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Ranking and Risk Factor Scheme for Malicious applications detection and Classifications

Author

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  • Kiran Khatter

    (School of Engineering and Technology, Ansal University, Gurgaon, India)

  • Sapna Malik

    (Maharaja Surajmal Institute of Technology, Delhi, India)

Abstract

Being an open source operating system, android mobiles are attacked by hundreds of malware every year. Moreover, malware are using many veiled techniques that makes it difficult to detect them. Android official markets and the Google Play Store are also not left untouched by malware. This article presents the Ranking and Risk Factor Scheme (RRFS), a hybrid intrusion detection technique for Android devices for the detection of malicious android applications. Ranking and risk factor schemes perform an analysis of Android permissions requested and system calls invoked features by ranking these features with some criteria and calculating the risk factor of each application for the detection and classification of malicious applications of 81 malware families. In the results, the ranking and risk factor scheme outperforms several related approaches and has the detection and classification performance of 99.2% and 88.7%, respectively and proved fast, an energy-efficient technique for resource constraint mobile device

Suggested Citation

  • Kiran Khatter & Sapna Malik, 2018. "Ranking and Risk Factor Scheme for Malicious applications detection and Classifications," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 9(3), pages 67-84, July.
  • Handle: RePEc:igg:jismd0:v:9:y:2018:i:3:p:67-84
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