Measuring Network Reputation in the Ad-Bidding Process

Yizheng Chen, Yacin Nadji, Rosa Romero-Gomez, Manos Antonakakis, and David Dagon
14th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 2017

Online advertising is a multi-billion dollar market, and therefore a target for abuse by Internet criminals. Prior work has shown millions of dollars of advertisers’ capital are lost due to ad abuse and focused on defense from the perspective of the end-host or the local network egress point. We investigate the potential of using public threat data to measure and detect adware and malicious affiliate traffic from the perspective of demand side platforms, which facilitate ad bidding between ad exchanges and advertisers. Our results show that malicious ad campaigns have statistically significant differences in traffic and lookup patterns from benign ones, however, public blacklists can only label a small percentage of ad publishers (0.27%), which suggests new lists dedicated to ad abuse should be created. Furthermore, we show malicious infrastructure on ad exchanges can be tracked with simple graph analysis and maliciousness heuristics.