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Detection of Malicious Applications in Android using Machine Learning

Abstract Details

2016, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
Android OS is one of the widely used mobile Operating Systems. Given Android’s popularity, the number of malicious applications and adwares are increasing constantly on par with the number of mobile devices. At present a great number of commercial signature based tools are available on the market which prevent to an extent the penetration and distribution of malicious applications. Numerous researches have been conducted which claims that traditional signature based detection system work well up to certain level and malware authors use numerous techniques to evade these tools. So given this state of affairs, there is an increasing need for an alternative, really tough malware detection system to complement and rectify the signature based system. Recent substantial research focused on machine learning algorithms that analyze features from malicious application and use those features to classify and detect unknown malicious applications. This thesis summarizes the usage of Text Mining or Information Retrieval Machine Learning algorithms used to detect malicious Android applications.
Anca Ralescu, Ph.D. (Committee Chair)
Chia Han, Ph.D. (Committee Member)
Dan Ralescu, Ph.D. (Committee Member)
67 p.

Recommended Citations

Citations

  • Baskaran, B. (2016). Detection of Malicious Applications in Android using Machine Learning [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128

    APA Style (7th edition)

  • Baskaran, Balaji. Detection of Malicious Applications in Android using Machine Learning. 2016. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128.

    MLA Style (8th edition)

  • Baskaran, Balaji. "Detection of Malicious Applications in Android using Machine Learning." Master's thesis, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128

    Chicago Manual of Style (17th edition)