Bot or Human: Identifying BotGenerated Clicks Using Machine Learning
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Typ
Examensarbete på kandidatnivå
Program
Publicerad
2021
Författare
BORG, FILIP
BROBECK, AXEL
KORTESAARI, SAGA
SKENDEROVIC, NERMIN
SUNDBOM, ARVID
SUNDSTRÖM, CHARLES
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
“I’m not a robot” is a common CAPTCHA (Completely Automated Public
Turing test to tell Computers and Humans Apart) often shown today upon
entering websites. The purpose behind the challenge is to distinguish hu mans from robots, or bots. However, the user experience becomes somewhat
intrusive and is not always viable for many websites. This project explores,
in collaboration with Prisjakt, how to retroactively identify clicks generated
by bots, using historical data and various machine learning models. The
models are trained and evaluated on the historical data in an effort to be
able to classify future clicks automatically. The result of the project is an
implementation of two models, a neural network and a gradient boosting
model, as well as an application programming interface (API) to use the
models with. The models show very promising results and suggest that an
automated system, which identifies clicks generated by bots, is possible.