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→Author obfuscation methods
The most rudimentary programs simply replace words with synonyms. More advanced programs change the complexity of the sentence structures.
The most rudimentary programs simply replace words with synonyms. More advanced programs change the complexity of the sentence structures.
One of the most advanced author obfuscation tools developed is Mutant-X.<ref>[https://github.com/asad1996172/Mutant-X Mutant X - Github]</ref>
The abstract for the 2019 journal article entitled ''A Girl Has No Name: Automated Authorship Obfuscation using Mutant-X'' published in ''Proceedings on Privacy Enhancing Technologies'' indicates:
{{Cquote|...a genetic algorithm based random search framework called Mutant-X which can automatically obfuscate text to successfully evade attribution while keeping the semantics of the obfuscated text similar to the original text. Specifically, Mutant-X sequentially makes changes in the text using mutation and crossover techniques while being guided by a fitness function that takes into account both attribution
probability and semantic relevance. While Mutant-X requires black-box knowledge of the adversary’s classifier, it does not require any additional training data and also works on documents of any length. We evaluate Mutant-X against a variety of authorship attribution methods on two different text corpora. Our results show that Mutant-X can decrease the accuracy of state-of-the-art authorship attribution methods by
as much as 64% while preserving the semantics much better than existing automated authorship obfuscation approaches.<ref>[https://content.sciendo.com/downloadpdf/journals/popets/2019/4/article-p54.pdf ''A Girl Has No Name: Automated Authorship Obfuscation using Mutant-X''] by Asad Mahmood, Faizan Ahmad, Zubair Shafiq, Padmini Srinivasan, and Fareed Zaffar, ''Proceedings on Privacy Enhancing Technologies''; 2019 (4):54–71</ref>}}
== See also ==
== See also ==