Click Fraud Detection and Prevention System For Ad Networks
Resumo
Click fraud detection consists of identifying the intention behind the clicks a system receives. A system that detects and prevents this type of fraud is proposed and implemented, based on the ad network, one of the 3 agents in the online ad environment. To validate, 3 servers were used, representing said agents. A bot simulates an attacker, and the frauds are ultimately identified by our proposed detector in tested scenarios.
Referências
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Clifford, S. (2009). Microsoft sues three in click-fraud scheme.
Court, U. S. D. (2009). Microsoft vs Eric Lam et. al.
Daswani, N. and Stoppelman, M. (2007). The anatomy of clickbot. a. In Proceedings of the first conference on First Workshop on Hot Topics in Understanding Botnets, pages 11–11. USENIX Association.
Fielding, R. and Reschke, J. (2014). Hypertext transfer protocol (http/1.1): Semantics and content. RFC 7231, RFC Editor. [link].
Human Benchmark (2018). Reaction time statistics. [link].
Kitts, B., Zhang, J. Y., Wu, G., Brandi, W., Beasley, J., Morrill, K., Ettedgui, J., Siddhartha, S., Yuan, H., Gao, F., et al. (2015). Click fraud detection: adversarial pattern recognition over 5 years at microsoft. In Real World Data Mining Applications, pages 181–201. Springer.
Leyden, J. (2006). Botnet implicated in click fraud scam.
McNair, C. (2017). Us ad spending: emarketer’s updated estimates and forecast for 2017.
Oentaryo, R. J., Lim, E.-P., Finegold, M., Lo, D., Zhu, F., Phua, C., Cheu, E.-Y., Yap, G.-E., Sim, K., Nguyen, M. N., et al. (2014). Detecting click fraud in online advertising: a data mining approach. Journal of Machine Learning Research, 15(1):99–140.
Priebe, J. (2009). A study of internet users’ cookie and javascript settings.
Thorpe, S., Fize, D., and Marlot, C. (1996). Speed of processing in the human visual system. nature, 381(6582):520.
Winnicki, A. (2016). Just how many web users really disable cookies or javascript?
Xu, H., Liu, D., Koehl, A., Wang, H., and Stavrou, A. (2014). Click fraud detection on the advertiser side. In European Symposium on Research in Computer Security, pages 419–438. Springer.
Publicado
25/10/2018
Como Citar
ALMEIDA, Paulo S. de; GONDIM, João J. C..
Click Fraud Detection and Prevention System For Ad Networks. In: WORKSHOP DE TRABALHOS DE INICIAÇÃO CIENTÍFICA E DE GRADUAÇÃO - SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 18. , 2018, Natal.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 189-192.
DOI: https://doi.org/10.5753/sbseg_estendido.2018.4157.
