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Non-email Spam and Machine Learning-Based Anti-spam Filters: Trends and Some Remarks

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Computer Aided Systems Theory – EUROCAST 2017 (EUROCAST 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10671))

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Abstract

Electronic spam, or unsolicited and undesired messages sent massively, is one of the threats that affects email and other media. The high volume and ratio of email spam have generated enormous time and economic losses. Due to this, many different email anti-spam defenses have been used. This translated into more complex spams in order to surpass them. Moreover, the spamming business moved to the less protected yet quite profitable non-email media because of the numerous potential targets that results from their extensive usage. Since that moment, spams in these media have increased rapidly in quantity, sophistication and danger, especially in the most popular ones: Instant Messaging, SMS and social media. Therefore, in this paper some of the characteristics and statistics of instant spam, mobile spam and social spam are exposed. Then, an overview of anti-spam techniques developed during the last decade to fight these new spam trends is presented, focusing on hybrid and Machine Learning-based approaches. We conclude with some possible future evolutionary steps of both non-email spams and anti-spams.

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Notes

  1. 1.

    http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/.

  2. 2.

    http://www.grumbletext.co.uk/ (website unavailable at the time of writing).

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Author information

Authors and Affiliations

  1. Universidad de Las Palmas de Gran Canaria (ULPGC), Las Palmas de Gran Canaria, Spain

    Ylermi Cabrera-León

  2. Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, San Cristóbal de La Laguna, Spain

    Patricio García Báez

  3. Instituto Universitario de Ciencias y Tecnologías Cibernéticas, Universidad de Las Palmas de Gran Canaria (ULPGC), Las Palmas de Gran Canaria, Spain

    Carmen Paz Suárez-Araujo

Authors
  1. Ylermi Cabrera-León
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  2. Patricio García Báez
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  3. Carmen Paz Suárez-Araujo
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Corresponding author

Correspondence to Carmen Paz Suárez-Araujo .

Editor information

Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Cabrera-León, Y., García Báez, P., Suárez-Araujo, C.P. (2018). Non-email Spam and Machine Learning-Based Anti-spam Filters: Trends and Some Remarks. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2017. EUROCAST 2017. Lecture Notes in Computer Science(), vol 10671. Springer, Cham. https://doi.org/10.1007/978-3-319-74718-7_30

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  • DOI: https://doi.org/10.1007/978-3-319-74718-7_30

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