6,427 research outputs found
Inefficiencies in Digital Advertising Markets
Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research
Web usage mining for click fraud detection
Estágio realizado na AuditMark e orientado pelo Eng.º Pedro FortunaTese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
The Effect of Third Party Investigation on Pay-Per-Click Advertising
Click fraud is a critical problem in pay-per-click advertising. While both service providers (SPs) and advertisers employ technologies to identify fraudulent clicks, prior work shows that they cannot be induced to make further improvements to their respective technologies. We consider the use of third-party investigation to address this problem and examine whether the responsibility of investigation payments helps induce both parties to work towards improving their technologies unilaterally. Using a principal-agent setting, we show that the advertiser always has incentives to improve his verification technology and the SP will improve his detection technology only when the detection cost is not too large. Given that the cost of detection technology is likely to be small due to the use of inexpensive online filters, our result suggests that third-party investigation helps induce further enhancements to the technologies and is a good mechanism to address the incentive problems in the click fraud setting
XRay: Enhancing the Web's Transparency with Differential Correlation
Today's Web services - such as Google, Amazon, and Facebook - leverage user
data for varied purposes, including personalizing recommendations, targeting
advertisements, and adjusting prices. At present, users have little insight
into how their data is being used. Hence, they cannot make informed choices
about the services they choose. To increase transparency, we developed XRay,
the first fine-grained, robust, and scalable personal data tracking system for
the Web. XRay predicts which data in an arbitrary Web account (such as emails,
searches, or viewed products) is being used to target which outputs (such as
ads, recommended products, or prices). XRay's core functions are service
agnostic and easy to instantiate for new services, and they can track data
within and across services. To make predictions independent of the audited
service, XRay relies on the following insight: by comparing outputs from
different accounts with similar, but not identical, subsets of data, one can
pinpoint targeting through correlation. We show both theoretically, and through
experiments on Gmail, Amazon, and YouTube, that XRay achieves high precision
and recall by correlating data from a surprisingly small number of extra
accounts.Comment: Extended version of a paper presented at the 23rd USENIX Security
Symposium (USENIX Security 14
Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations
In the last years, cryptocurrencies are increasingly popular. Even people who
are not experts have started to invest in these securities and nowadays
cryptocurrency exchanges process transactions for over 100 billion US dollars
per month. However, many cryptocurrencies have low liquidity and therefore they
are highly prone to market manipulation schemes. In this paper, we perform an
in-depth analysis of pump and dump schemes organized by communities over the
Internet. We observe how these communities are organized and how they carry out
the fraud. Then, we report on two case studies related to pump and dump groups.
Lastly, we introduce an approach to detect the fraud in real time that
outperforms the current state of the art, so to help investors stay out of the
market when a pump and dump scheme is in action.Comment: Accepted for publication at The 29th International Conference on
Computer Communications and Networks (ICCCN 2020
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