A Survey on Malware Detection Techniques on Linux Powered Smart Phones using Machine Learning Approaches

  • Authors

    • Mr. Rahul Y. Pawar
    • Dr C.Mahesh
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.18706
  • smart phones, System calls, targets, malwares, machine learning, ptrace.

  • Abstract

    Mobile Phone manufacturers are continuously working to take move on with rapid pace on their new models and to match with the need of customer, they need to customize their system. However the security scenarios of such practice are not that known, due to this various malware and viruses are increasing day by day and causing harm to the devices. Due to the substantial damage caused by malware in last few years certain significant efforts on developing detection and defense mechanism against malwares. For detecting such malicious applications and malwares a security system should be developed which will target such anomaly or outliers in system. In data mining anomaly detection system plays a major role by monitoring the behavior of an application and categorizing them in to normal and abnormal to detect malwares present in the system.

     

     

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  • How to Cite

    Rahul Y. Pawar, M., & C.Mahesh, D. (2018). A Survey on Malware Detection Techniques on Linux Powered Smart Phones using Machine Learning Approaches. International Journal of Engineering & Technology, 7(3.34), 8-14. https://doi.org/10.14419/ijet.v7i3.34.18706

    Received date: 2018-09-01

    Accepted date: 2018-09-01

    Published date: 2018-09-01