1. bookVolumen 11 (2021): Heft 4 (October 2021)
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
2449-6499
Erstveröffentlichung
30 Dec 2014
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch
Uneingeschränkter Zugang

Decision Making Support System for Managing Advertisers By Ad Fraud Detection

Online veröffentlicht: 08 Oct 2021
Volumen & Heft: Volumen 11 (2021) - Heft 4 (October 2021)
Seitenbereich: 331 - 339
Akzeptiert: 22 Sep 2021
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
2449-6499
Erstveröffentlichung
30 Dec 2014
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

[1] AsSadhan, B., Moura, J.M., Lapsley, D., Jones, C., Strayer, W.T.: Detecting botnets using command and control traffic. In: 2009 Eighth IEEE International Symposium on Network Computing and Applications, pp. 156–162. IEEE (2009)10.1109/NCA.2009.56 Search in Google Scholar

[2] Bengio, Y.: Learning deep architectures for AI. Now Publishers Inc (2009)10.1561/9781601982957 Search in Google Scholar

[3] Chen, C.M., Lin, H.C.: Detecting botnet by anomalous traffic. journal of information security and applications 21, 42–51 (2015)10.1016/j.jisa.2014.05.002 Search in Google Scholar

[4] eMarketer: Digital ad fraud 2019. https://www.emarketer.com/content/digital-ad-fraud-2019 Search in Google Scholar

[5] Glorot, X., Bordes, A., Bengio, Y.: Deep sparse rectifier neural networks. In: Proceedings of the fourteenth international conference on artificial intelligence and statistics, pp. 315–323. JMLR Workshop and Conference Proceedings (2011) Search in Google Scholar

[6] Lagopoulos, A., Tsoumakas, G., Papadopoulos, G.: Web robot detection in academic publishing. arXiv preprint arXiv:1711.05098 (2017) Search in Google Scholar

[7] Neal, A., Kouwenhoven, S., Sa, O.: Quantifying online advertising fraud: Ad-click bots vs humans. In: Tech. Rep. Oxford Bio Chronometrics (2015) Search in Google Scholar

[8] Networks, D.: 2018 bad bot report. https://resources.distilnetworks.com/whitepapers/2018-bad-bot-report Search in Google Scholar

[9] Rajaraman, A., Ullman, J.D.: Mining of massive datasets. Cambridge University Press (2011)10.1017/CBO9781139058452 Search in Google Scholar

[10] Research, J.: Ad fraud - how ai will rescue your budget. https://news.unilead.net/wp-content/uploads/2017/09/Ad-Fraud-How-AI-will-rescueyour-Budget-whitepaper.pdf Search in Google Scholar

[11] Seyyar, M.B., Çatak, F.Ö., Gül, E.: Detection of attack-targeted scans from the apache httpserver access logs. Applied computing and informatics 14(1), 28–36 (2018)10.1016/j.aci.2017.04.002 Search in Google Scholar

[12] Silva, S.S., Silva, R.M., Pinto, R.C., Salles, R.M.: Botnets: A survey. Computer Networks 57(2), 378–403 (2013)10.1016/j.comnet.2012.07.021 Search in Google Scholar

[13] Soniya, B., Wilscy, M.: Detection of randomized bot command and control traffic on an end-point host. Alexandria Engineering Journal 55(3), 2771–2781 (2016)10.1016/j.aej.2016.04.004 Search in Google Scholar

[14] Zhu, X., Tao, H., Wu, Z., Cao, J., Kalish, K., Kayne, J.: Fraud prevention in online digital advertising. Springer (2017)10.1007/978-3-319-56793-8 Search in Google Scholar

Empfohlene Artikel von Trend MD

Planen Sie Ihre Fernkonferenz mit Scienceendo