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Detection of Avionics Supply Chain Non-control-flow Malware Using Binary Decompilation and Wavelet Analysis

Hill, Jeremy Michael Olivar
http://orcid.org/0000-0002-7106-0524
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1628159084278194

Abstract Details

2021, Master of Science in Computer Engineering, University of Dayton, Electrical and Computer Engineering.
Non-control-flow Trojans pose a threat to decision-making data in embedded systems. By evading typical third party testing by remaining always-on and only effecting a small localized region of the input data, the output data is skewed just enough to have decisions made just sooner or just later than originally intended. Using the Ghidra decompiler and the discrete wavelet transform, the capability to extract a binary's functional behavior, represent it in a waveform, and uncover anomalies, aka localized behaviors, is posited. Using Ghidra, a sense of the functional behavior of a simple program is obtained, and a Monte Carlo simulation of phase shifted Bessel functions of the first kind with a Gaussian Trojan of random magnitude (aka amplitude), location (aka mean), and breadth (aka variance) is completed. The discrete wavelet transform is able to uncover highly-localized anomalies.
Temesguen Kebede (Committee Chair)
David Kapp (Committee Member)
Keigo Hirakawa (Committee Member)
53 p.
Computer Engineering; Computer Science; Electrical Engineering
non-control-flow Trojans; decompilation; Ghidra; wavelet analysis; discrete wavelet transform

Recommended Citations

Citations

  • Hill, J. M. O. (2021). Detection of Avionics Supply Chain Non-control-flow Malware Using Binary Decompilation and Wavelet Analysis [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1628159084278194

    APA Style (7th edition)

  • Hill, Jeremy. Detection of Avionics Supply Chain Non-control-flow Malware Using Binary Decompilation and Wavelet Analysis. 2021. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1628159084278194.

    MLA Style (8th edition)

  • Hill, Jeremy. "Detection of Avionics Supply Chain Non-control-flow Malware Using Binary Decompilation and Wavelet Analysis." Master's thesis, University of Dayton, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1628159084278194

    Chicago Manual of Style (17th edition)

dayton1628159084278194
394
© 2021, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.