TY - GEN
T1 - A security analysis of the facebook ad library
AU - Edelson, Laura
AU - Lauinger, Tobias
AU - McCoy, Damon
N1 - Funding Information:
First, we wish to acknowledge the efforts that the Facebook Ad Library team have put into building this product that enabled our analysis, and their willingness to work with us to improve it. We also thank Facebook employees for their insightful comments on earlier drafts of this paper. This work was funded by the NSF through grants 1717062 and 1814816, as well as by gifts from Democracy Fund and the Luminate Group. Our research lab has also received gifts from Google. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the view of our funders.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Actors engaged in election disinformation are using online advertising platforms to spread political messages. In response to this threat, online advertising networks have started making political advertising on their platforms more transparent in order to enable third parties to detect malicious advertisers. We present a set of methodologies and perform a security analysis of Facebook's U.S. Ad Library, which is their political advertising transparency product. Unfortunately, we find that there are several weaknesses that enable a malicious advertiser to avoid accurate disclosure of their political ads. We also propose a clustering-based method to detect advertisers engaged in undeclared coordinated activity. Our clustering method identified 16 clusters of likely inauthentic communities that spent a total of over four million dollars on political advertising. This supports the idea that transparency could be a promising tool for combating disinformation. Finally, based on our findings, we make recommendations for improving the security of advertising transparency on Facebook and other platforms.
AB - Actors engaged in election disinformation are using online advertising platforms to spread political messages. In response to this threat, online advertising networks have started making political advertising on their platforms more transparent in order to enable third parties to detect malicious advertisers. We present a set of methodologies and perform a security analysis of Facebook's U.S. Ad Library, which is their political advertising transparency product. Unfortunately, we find that there are several weaknesses that enable a malicious advertiser to avoid accurate disclosure of their political ads. We also propose a clustering-based method to detect advertisers engaged in undeclared coordinated activity. Our clustering method identified 16 clusters of likely inauthentic communities that spent a total of over four million dollars on political advertising. This supports the idea that transparency could be a promising tool for combating disinformation. Finally, based on our findings, we make recommendations for improving the security of advertising transparency on Facebook and other platforms.
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U2 - 10.1109/SP40000.2020.00084
DO - 10.1109/SP40000.2020.00084
M3 - Conference contribution
AN - SCOPUS:85091594235
T3 - Proceedings - IEEE Symposium on Security and Privacy
SP - 661
EP - 678
BT - Proceedings - 2020 IEEE Symposium on Security and Privacy, SP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st IEEE Symposium on Security and Privacy, SP 2020
Y2 - 18 May 2020 through 21 May 2020
ER -