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Evolution of Spamming Attacks on Facebook

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Information Security Applications (WISA 2017)

Abstract

Defence techniques against spamming attack have been introduced and developed in many different areas, such as e-mail, web, and even social network service, over the past decades. Whereas, we have still been suffering from the attack though the service vendors as well as academia have been making best effort on winning such arms race. Such being the case, Facebook have also been inevitable to confront spamming campaign in order not to be overwhelmed by massive junk messages. Certain spamming patterns have recently been remarkably common on Facebook which collaborates with other social network messenger. We study such the advanced spamming campaign so as to demystify how it has been worked and settled down on Facebook ecosystem. We build a crawler and analyser which collect 0.6 million of comments; afterwards, extracts the targeted spams. Our data shows that the spams are systematic, well-structured, obfuscated and even localized.

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References

  1. Appstickers: Kakao Talk: 152 Million Users and 93% Market Share in South Korea. http://appstickers.net/kakao-talk-152-million-users-and-93-market-share-in-south-korea/. Accessed 1 Jan 2016

  2. Abu-Nimeh, S., Chen, T.M., Alzubi, O.: A Survey of Malicious and Spam Posts in Facebook (2011)

    Google Scholar 

  3. Ahmed, F., Abulaish, M.: A generic statistical approach for spam detection in Online Social Networks. Comput. Commun. 36(10), 1120–1129 (2013)

    Article  Google Scholar 

  4. DMR: By the Numbers: 200 Surprising Facebook Statistics. http://expandedramblings.com/index.php/by-the-numbers-17-amazing-facebook-stats/. Accessed 1 Jan 2016

  5. Jin, X., Lin, C., Luo, J., Han, J.: A data mining-based spam detection system for social media networks. Proc. VLDB Endow. 4(12), 1458–1461 (2011)

    Google Scholar 

  6. Rahman, M.S., Huang, T.K., Madhyastha, H.V., Faloutsos, M.: Efficient and scalable socware detection in online social networks. Presented as Part of the 21st USENIX Security Symposium (USENIX Security 2012), pp. 663–678 (2012)

    Google Scholar 

  7. Stein, T., Chen, E., Mangla, K.: Facebook immune system. In: Proceedings of the 4th Workshop on Social Network Systems (ACM), p. 8 (2011)

    Google Scholar 

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Acknowledgements

This research was supported by the Korea Government (the Ministry of Science, ICT and Future Planning) under Basic Science Research Program (NRF-2013R1A1A3009163) through the National Research Foundation of Korea (NRF), and supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (No. NRF-2016M3C4A7937117).

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Correspondence to Ji Sun Shin .

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Lee, M., Lee, H., Shin, J.S. (2018). Evolution of Spamming Attacks on Facebook. In: Kang, B., Kim, T. (eds) Information Security Applications. WISA 2017. Lecture Notes in Computer Science(), vol 10763. Springer, Cham. https://doi.org/10.1007/978-3-319-93563-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-93563-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93562-1

  • Online ISBN: 978-3-319-93563-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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