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Analysis of Smartphone Traffic

Abstract Details

2015, Master of Science in Electrical Engineering, Cleveland State University, Washkewicz College of Engineering.
Smartphone reconnaissance, the first step to launch security attacks on a target smartphone, enables an adversary to tailor attacks by exploiting the known vulnerabilities of the target system. We investigate smartphone OS identification with encrypted traffic in this paper. Four identification algorithms based on the spectral analysis of the encrypted traffic are proposed. The identification algorithms are designed for high identification accuracy by removing noise frequency components and for high efficiency in terms of computation complexity. We evaluate the identification algorithms with smartphone traffic collected over three months. The experimental results show that the algorithms can identify the smartphone OS accurately. The identification accuracy can reach 100% with only 30 seconds of smartphone traffic.
Ye Zhu, PhD (Advisor)
Chansu Yu, PhD (Committee Member)
Yuanjian Fu, PhD (Committee Member)

Recommended Citations

Citations

  • Ruffing, N. L. (2015). Analysis of Smartphone Traffic [Master's thesis, Cleveland State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=csu1430150923

    APA Style (7th edition)

  • Ruffing, Nicholas. Analysis of Smartphone Traffic. 2015. Cleveland State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=csu1430150923.

    MLA Style (8th edition)

  • Ruffing, Nicholas. "Analysis of Smartphone Traffic." Master's thesis, Cleveland State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=csu1430150923

    Chicago Manual of Style (17th edition)