Set of obfuscated spam dataset by using LeetSpeak transformations

  1. De Mendizabal, Iñaki Velez 1
  2. Vidriales, Xabier 1
  3. Fernandes, Vitor Basto 2
  4. Ezpeleta, Enaitz 1
  5. Méndez, José Ramón 3
  6. Zurutuza, Urko 1
  1. 1 Universidad de Mondragón/Mondragon Unibertsitatea
    info

    Universidad de Mondragón/Mondragon Unibertsitatea

    Mondragón, España

    ROR https://ror.org/00wvqgd19

  2. 2 Instituto Universitário de Lisboa (ISCTE-IUL)
  3. 3 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

Erakutsi afiliazioak +

Argitaratzaile: Zenodo

Argitalpen urtea: 2022

Mota: Dataset

CC BY 4.0

DOI: 10.5281/ZENODO.6373653 lock_openSarbide irekia editor

Laburpena

The usage of LeetSpeak and other text hiding tricks is often used by spammers in the distribution of unsolicited contents. To evaluate deobfuscation techniques and their impact on spam content classification, we preprocessed several popular public datasets to partially obfuscate the text. The datasets transformed are: YouTube Spam Collection [2, 3] which is available on https://www.dt.fee.unicamp.br/~tiago/youtubespamcollection/. a subset of YouTube Comments [4, 5] which is available on http://mlg.ucd.ie/yt/. CSDMC2010 which is available on http://csmining.org/index.php/spam-email-datasets-.html. TREC2007 which is available on https://plg.uwaterloo.ca/~gvcormac/treccorpus07/