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Observer Effect: How Intercepting HTTPS Traffic Forces Malware to Change Their Behavior

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 790))

Abstract

During the last couple of years there has been an important surge on the use of HTTPs by malware. The reason for this increase is not completely understood yet, but it is hypothesized that it was forced by organizations only allowing web traffic to the Internet. Using HTTPs makes malware behavior similar to normal connections. Therefore, there has been a growing interest in understanding the usage of HTTPs by malware. This paper describes our research to obtain large quantities of real malware traffic using HTTPs, our use of man-in-the-middle HTTPs interceptor proxies to open and study the content, and our analysis of how the behavior of the malware changes after being intercepted. The research goal is to understand how malware uses HTTPs and the impact of intercepting its traffic. We conclude that the use of an interceptor proxy forces the malware to change its behavior and therefore should be carefully considered before being implemented.

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Notes

  1. 1.

    https://mitmproxy.org/.

  2. 2.

    https://www.cacti.net/.

  3. 3.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-169-1/.

  4. 4.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-169-2/.

  5. 5.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-192-2/.

  6. 6.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-192-1/.

  7. 7.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-192-3/.

  8. 8.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-219-1/.

  9. 9.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-219-2/.

  10. 10.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-208-1/.

  11. 11.

    https://mcfp.felk.cvut.cz/publicDatasets/CTU-Malware-Capture-Botnet-208-2/.

References

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  3. Lokoč, J., Kohout, J., Čech, P., Skopal, T., Pevný, T.: k-NN classification of Malware in HTTPS traffic using the metric space approach. In: Chau, M., Wang, G.Alan, Chen, H. (eds.) PAISI 2016. LNCS, vol. 9650, pp. 131–145. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-31863-9_10

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  8. Stratosphere Dataset. https://stratosphereips.org/category/dataset.html

  9. Nomad Project. https://stratosphereips.org/category/Nomad.html

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Correspondence to María José Erquiaga .

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Erquiaga, M.J., García, S., Garino, C.G. (2018). Observer Effect: How Intercepting HTTPS Traffic Forces Malware to Change Their Behavior. In: De Giusti, A. (eds) Computer Science – CACIC 2017. CACIC 2017. Communications in Computer and Information Science, vol 790. Springer, Cham. https://doi.org/10.1007/978-3-319-75214-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-75214-3_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75213-6

  • Online ISBN: 978-3-319-75214-3

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