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IPv6 OS Fingerprinting Methods: Review

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Advances in Visual Informatics (IVIC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10645))

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Abstract

IPv6 is the new communication protocol which will eventually replace IPv4 is suffering from different security issues. As an initial step to understand IPv6 networks and their vulnerabilities it is of critical importance to identify the characteristics of the connected devices. Detecting the OS fingerprints of these devices is one of these characteristics that are essential to identifying the vulnerabilities of each of them. Currently, few OS detection methods have supported IPv6 protocol, as it did not fully replace IPv4 yet. This paper attempts to describe the existing methods of OS fingerprinting with IPv6, as well as their challenges and limitations. Moreover, this paper studies the available datasets that might be used for IPv6 OS fingerprinting. By understanding the existing methods and datasets, the reader can figure out the current needs for proposing new OS fingerprinting methods for IPv6 protocol.

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References

  1. ABI Research: The Internet of Things will Drive Wireless Connected Devices to 40.9 Billion in 2020. ABI Research (2014). https://www.abiresearch.com/press/the-internet-of-things-will-drive-wireless-connect/

  2. Elejla, O.E., Anbar, M., Belaton, B.: ICMPv6-based DoS and DDoS attacks and defense mechanisms. IETE Tech. Rev. 1–18 (2016). doi:10.1080/02564602.2016.1192964

  3. Elejla, O.E., Belaton, B., Anbar, M., Alnajjar, A.: Intrusion detection systems of ICMPv6-based DDoS attacks. Neural Comput. Appl. 28, 1–12 (2016)

    Article  Google Scholar 

  4. Schwartzenberg, J.: Using machine learning techniques for advanced passive operating system fingerprinting. Master thesis, University of Twente (2010)

    Google Scholar 

  5. Srisuresh, P., Egevang, K.: Traditional IP network address translator (Traditional NAT) (2000)

    Google Scholar 

  6. Ornaghi, A., Valleri, M.: Ettercap (2005). http://ettercap.github.io/ettercap/ (2017)

  7. Yarochkin, F., Kydyraliev, M., Arkin, O.: Xprobe project (2014). http://x-probe.org/ (2017)

  8. Lyon, G.: Nmap–free security scanner for network exploration & security audits (2009). https://nmap.org/ (2017)

  9. Greenwald, L.G., Thomas, T.J.: Toward undetected operating system fingerprinting. WOOT 7, 1–10 (2007)

    Google Scholar 

  10. Stopforth, R.: Techniques and countermeasures of TCP/IP OS fingerprinting on Linux Systems. Thesis, University of KwaZulu-Natal, Durban (2007)

    Google Scholar 

  11. Auffret, P.: SinFP, January 2007. http://www.gomor.org/sinfp (2017)

  12. Beck, F., Festor, O., Chrisment, I.: IPv6 neighbor discovery protocol based OS fingerprinting, Inria (2007)

    Google Scholar 

  13. Biondi, P.: Scapy (2011). http://www.secdev.org/projects/scapy/ (2015)

  14. Matoušek, P., Ryšavý, O., Grégr, M., Vymlátil, M.: Towards identification of operating systems from the internet traffic: IPFIX monitoring with fingerprinting and clustering. In: 2014 5th International Conference on Data Communication Networking (DCNET), pp. 1–7. IEEE (2014)

    Google Scholar 

  15. Prigent, G., Vichot, F., Harrouet, F.: IpMorph: fingerprinting spoofing unification. J. Comput. Virol. 6(4), 329–342 (2010)

    Article  Google Scholar 

  16. Nerakis, E.: IPv6 host fingerprint. Master DTIC Document, Naval Postgraduate School (2006)

    Google Scholar 

  17. Zalewski, M.: P0f: Passive OS Fingerprinting Tool (2006). http://lcamtuf.coredump.cx/p0f3/ (2017)

  18. Jajodia, S., Subrahmanian, V.S., Swarup, V., Wang, C.: Cyber Deception: Building the Scientific Foundation. Springer International Publishing, Switzerland (2016). doi:10.1007/978-3-319-32699-3

    Book  Google Scholar 

  19. Fifield, D., Geana, A., MartinGarcia, L., Morbitzer, M., Tygar, J.D.: Remote operating system classification over IPv6. In: Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security, pp. 57–67. ACM (2015)

    Google Scholar 

  20. IRL Fingerprinting Dataset (2014). http://irl.cs.tamu.edu/projects/sampling/ (2017)

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Correspondence to Omar E. Elejla .

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Elejla, O.E., Belaton, B., Anbar, M., Alijla, B.O. (2017). IPv6 OS Fingerprinting Methods: Review. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2017. Lecture Notes in Computer Science(), vol 10645. Springer, Cham. https://doi.org/10.1007/978-3-319-70010-6_61

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  • DOI: https://doi.org/10.1007/978-3-319-70010-6_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70009-0

  • Online ISBN: 978-3-319-70010-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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