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Methods to Detect Cyberthreats on Twitter

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Surveillance in Action

Abstract

Twitter is a microblogging service where users can post short messages and communicate with millions of users instantaneously. Twitter has been used for marketing, political campaigns, and during catastrophic events. Unfortunately, Twitter has been exploited by spammers and cybercriminals to post spam, spread malware, and launch different kinds of cyberattacks. The ease of following another user on Twitter, the posting of shortened URLs in tweets, the use of trending hashtags in tweets, and so on, have made innocent users the victims of various cyberattacks. This chapter reviews recent methods to detect spam, spammers, cybercus content, and suspicious users on Twitter. It also presents a unified framework for modeling hreats on Twitter are discussed, specifically in the context of big data and adversarial machine learning.

Approved for Public Release; Distribution Unlimited: 88ABW-2017-1553, dated 05 Apr 2017.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Social_spam.

  2. 2.

    For example, http://google.com.

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Acknowledgements

This work was performed while the first author held an NRC Research Associateship award at Air Force Research Lab, Rome, New York. The authors would like to thank the anonymous reviewers for their comments and suggestions, and Anas Katib for his assistance.

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Authors and Affiliations

  1. Department of Computer Science and Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO, USA

    Praveen Rao

  2. Cyber Assurance Branch, Air Force Research Lab, Rome, NY, USA

    Charles Kamhoua, Laurent Njilla & Kevin Kwiat

Authors
  1. Praveen Rao
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  2. Charles Kamhoua
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  3. Laurent Njilla
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  4. Kevin Kwiat
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Corresponding author

Correspondence to Praveen Rao .

Editor information

Editors and Affiliations

  1. Department of Informatics and Computers, Hellenic Air Force Academy, Attica, Greece

    Panagiotis Karampelas

  2. Multispectral Imagery Lab, Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, West Virginia, USA

    Thirimachos Bourlai

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Rao, P., Kamhoua, C., Njilla, L., Kwiat, K. (2018). Methods to Detect Cyberthreats on Twitter. In: Karampelas, P., Bourlai, T. (eds) Surveillance in Action. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-68533-5_16

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