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Malvertising in Facebook: Analysis, Quantification and Solution

1
Department of Telematic Engineering, Universidad Carlos III de Madrid, 28911 Leganés, Spain
2
UC3M-Santander Big Data Institute, 28903 Getafe, Spain
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(8), 1332; https://doi.org/10.3390/electronics9081332
Received: 30 June 2020 / Revised: 27 July 2020 / Accepted: 13 August 2020 / Published: 18 August 2020
(This article belongs to the Section Computer Science & Engineering)
Online advertising is a wealthy industry that generated more than $100B in 2018 only in the US and delivers billions of ads to Internet users every day with. These impressive numbers have also attracted the attention of malicious players that try to exploit the online advertising ecosystem for their own benefit. In particular, one of the most harmful practices refers to malicious users that act as advertisers to deliver unsafe ads. The goal of these ads is to compromise the security of the users that receive those ads. This practice is referred to as Malvertising. Some reports have estimated the economic loss caused by malvertising to the online advertising sector to $1.1B in 2017. This paper is the first work that analyses and quantifies the impact of malvertising in Facebook. To accomplish this study, we rely on a dataset that includes more than 5 M ads delivered to 3 K Facebook users from 126 K advertisers between October 2016 and May 2018. Our results reveal that although the portion of advertisers (0.68%) and ads (0.17%) associated to malvertising is very low, 1/3 of the users in our study were exposed to malvertising. Finally, we also propose a novel solution to block malvertising ads in real-time in Facebook. View Full-Text
Keywords: Facebook; online advertising; cybersecurity; malvertising; transparency Facebook; online advertising; cybersecurity; malvertising; transparency
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MDPI and ACS Style

Arrate, A.; González-Cabañas, J.; Cuevas, Á.; Cuevas, R. Malvertising in Facebook: Analysis, Quantification and Solution. Electronics 2020, 9, 1332. https://doi.org/10.3390/electronics9081332

AMA Style

Arrate A, González-Cabañas J, Cuevas Á, Cuevas R. Malvertising in Facebook: Analysis, Quantification and Solution. Electronics. 2020; 9(8):1332. https://doi.org/10.3390/electronics9081332

Chicago/Turabian Style

Arrate, Aritz, José González-Cabañas, Ángel Cuevas, and Rubén Cuevas. 2020. "Malvertising in Facebook: Analysis, Quantification and Solution" Electronics 9, no. 8: 1332. https://doi.org/10.3390/electronics9081332

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