The Dark Alleys of Madison Avenue: Understanding Malicious Advertisements (original) (raw)

Measuring Abuse in Web Push Advertising

ArXiv, 2020

The rapid growth of online advertising has fueled the growth of ad-blocking software, such as new ad-blocking and privacy-oriented browsers or browser extensions. In response, both ad publishers and ad networks are constantly trying to pursue new strategies to keep up their revenues. To this end, ad networks have started to leverage the Web Push technology enabled by modern web browsers. As web push notifications (WPNs) are relatively new, their role in ad delivery has not been yet studied in depth. Furthermore, it is unclear to what extent WPN ads are being abused for malvertising (i.e., to deliver malicious ads). In this paper, we aim to fill this gap. Specifically, we propose a system called PushAdMiner that is dedicated to (1) automatically registering for and collecting a large number of web-based push notifications from publisher websites, (2) finding WPN-based ads among these notifications, and (3) discovering malicious WPN-based ad campaigns. Using PushAdMiner, we collected ...

Automated Malicious Advertisement Detection using VirusTotal, URLVoid, and TrendMicro

8th International Conference on Information and Communication Systems (ICICS 2017), 2017

—The Internet economy is based on free access to content in exchange of viewing advertisements that might lead to online purchases. Advertisements represent an important source of revenue to Advertising companies. Those companies employ every possible technique and trick to maximize clicks and visits to advertisers' websites. Modern websites exchange advertisement contents from ads' providers (such as Google AdSense), which means they do not control the contents of those advertisements. Although large providers such as Google and Yahoo! are supposed to be trustworthy, ad arbitration allows them to auction of those ad slots to other providers. Therefore, web administrators cannot guarantee the source of the ads on their delegated website areas. Those advertisements contain Javascript and may redirect to malicious websites which might lead to malicious code being executed or malware being installed. This paper proposes and implements a system for automatically detecting malicious advertisements. It employs three different online malware domain detections systems (VirusTotal, URLVoid, and TrendMicro) for malicious advertisements detection purposes and reports the number of detected malicious advertisements using each system. In addition, we study the efficiency of each system by calculating the confusion matrix and accuracy. We find that URLVoid is the best in terms of accuracy (73%) because it uses a combination of well known website scanners and domain blacklists.

Threats involved with internet advertisements and attack on botnet network

After the research on online advertisement industries, the global committees have identified various threats and risks to consumer's privacy and security which are hidden by the consumer. Various malicious software (malware) attacks take place through online advertisements without any click or interaction by user with advertisements contents. The scope of this research is to identify such threats and provide ideas to counter attack on botnet network to prevent privacy and financial loss.

Tracing Information Flows Between Ad Exchanges Using Retargeted Ads

2016

Numerous surveys have shown that Web users are concerned about the loss of privacy associated with online tracking. Alarmingly, these surveys also reveal that people are also unaware of the amount of data sharing that occurs between ad exchanges, and thus underestimate the privacy risks associated with online tracking. In reality, the modern ad ecosystem is fueled by a flow of user data between trackers and ad exchanges. Although recent work has shown that ad exchanges routinely perform cookie matching with other exchanges, these studies are based on brittle heuristics that cannot detect all forms of information sharing, especially under adversarial conditions. In this study, we develop a methodology that is able to detect client- and server-side flows of information between arbitrary ad exchanges. Our key insight is to leverage retargeted ads as a tool for identifying information flows. Intuitively, our methodology works because it relies on the semantics of how exchanges serve ads...

Ads and Fraud: A Comprehensive Survey of Fraud in Online Advertising

Journal of Cybersecurity and Privacy, 2021

Over the last two decades, we have witnessed a fundamental transformation of the advertising industry, which has been steadily moving away from the traditional advertising mediums, such as television or direct marketing, towards digital-centric and internet-based platforms. Unfortunately, due to its large-scale adoption and significant revenue potential, digital advertising has become a very attractive and frequent target for numerous cybercriminal groups. The goal of this study is to provide a consolidated view of different categories of threats in the online advertising ecosystems. We begin by introducing the main elements of an online ad platform and its different architecture and revenue models. We then review different categories of ad fraud and present a taxonomy of known attacks on an online advertising system. Finally, we provide a comprehensive overview of methods and techniques for the detection and prevention of fraudulent practices within those system—both from the scien...