Bot detection algorithms: A systematic literature review

Hélder João Chissingui, Humberto Díaz Pando, Mailyn Moreno Espino, Nayma Cepero Pérez

Resumen


The growing adoption of web-based services contributes a lot to the growing trend of the use of bots. Despite its benefits, malicious intent by attackers is even more worrisome. Issues such as cyber attacks, cognitive warfare, are at the origin of malicious activities that damage the security properties of systems and manipulate public opinion. In recent years, the number of studies based on this topic has grown considerably, although there have been very few systematic literature review studies. In this article, a generic studies is made on the different ways of detecting bots, describing the approaches and their functional particularities. The tools for building and evaluating bot detection systems are described, such as, datasets, features, performance metrics, development frameworks, as well as, a comparative study of the most used programming language. Also, the defence measures against malicious bots are exposed, in addition to a discussion about the adequacy of the bot detection approaches.

Palabras clave


Bot detection algorithms, malicious bots, systematic literature review

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La Universidad de las Ciencias Informáticas (UCI), a través del sello editorial Ediciones Futuro, publica los contenidos de la Revista Cubana de Ciencias Informáticas (RCCI) bajo licencia Creative Commons de tipo Atribución 4.0 Internacional (CC BY 4.0). Esta licencia permite a otros distribuir, mezclar, ajustar y construir a partir de su obra, incluso con fines comerciales, siempre que le sea reconocida la autoría de la creación original.
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