5,805 research outputs found
Third Party Tracking in the Mobile Ecosystem
Third party tracking allows companies to identify users and track their
behaviour across multiple digital services. This paper presents an empirical
study of the prevalence of third-party trackers on 959,000 apps from the US and
UK Google Play stores. We find that most apps contain third party tracking, and
the distribution of trackers is long-tailed with several highly dominant
trackers accounting for a large portion of the coverage. The extent of tracking
also differs between categories of apps; in particular, news apps and apps
targeted at children appear to be amongst the worst in terms of the number of
third party trackers associated with them. Third party tracking is also
revealed to be a highly trans-national phenomenon, with many trackers operating
in jurisdictions outside the EU. Based on these findings, we draw out some
significant legal compliance challenges facing the tracking industry.Comment: Corrected missing company info (Linkedin owned by Microsoft). Figures
for Microsoft and Linkedin re-calculated and added to Table
Privacy Implications of Health Information Seeking on the Web
This article investigates privacy risks to those visiting health- related web
pages. The population of pages analyzed is derived from the 50 top search
results for 1,986 common diseases. This yielded a total population of 80,124
unique pages which were analyzed for the presence of third-party HTTP requests.
91% of pages were found to make requests to third parties. Investigation of
URIs revealed that 70% of HTTP Referer strings contained information exposing
specific conditions, treatments, and diseases. This presents a risk to users in
the form of personal identification and blind discrimination. An examination of
extant government and corporate policies reveals that users are insufficiently
protected from such risks
MobileAppScrutinator: A Simple yet Efficient Dynamic Analysis Approach for Detecting Privacy Leaks across Mobile OSs
Smartphones, the devices we carry everywhere with us, are being heavily
tracked and have undoubtedly become a major threat to our privacy. As "tracking
the trackers" has become a necessity, various static and dynamic analysis tools
have been developed in the past. However, today, we still lack suitable tools
to detect, measure and compare the ongoing tracking across mobile OSs. To this
end, we propose MobileAppScrutinator, based on a simple yet efficient dynamic
analysis approach, that works on both Android and iOS (the two most popular OSs
today). To demonstrate the current trend in tracking, we select 140 most
representative Apps available on both Android and iOS AppStores and test them
with MobileAppScrutinator. In fact, choosing the same set of apps on both
Android and iOS also enables us to compare the ongoing tracking on these two
OSs. Finally, we also discuss the effectiveness of privacy safeguards available
on Android and iOS. We show that neither Android nor iOS privacy safeguards in
their present state are completely satisfying
Control What You Include! Server-Side Protection against Third Party Web Tracking
Third party tracking is the practice by which third parties recognize users
accross different websites as they browse the web. Recent studies show that 90%
of websites contain third party content that is tracking its users across the
web. Website developers often need to include third party content in order to
provide basic functionality. However, when a developer includes a third party
content, she cannot know whether the third party contains tracking mechanisms.
If a website developer wants to protect her users from being tracked, the only
solution is to exclude any third-party content, thus trading functionality for
privacy. We describe and implement a privacy-preserving web architecture that
gives website developers a control over third party tracking: developers are
able to include functionally useful third party content, the same time ensuring
that the end users are not tracked by the third parties
Measuring third party tracker power across web and mobile
Third-party networks collect vast amounts of data about users via web sites
and mobile applications. Consolidations among tracker companies can
significantly increase their individual tracking capabilities, prompting
scrutiny by competition regulators. Traditional measures of market share, based
on revenue or sales, fail to represent the tracking capability of a tracker,
especially if it spans both web and mobile. This paper proposes a new approach
to measure the concentration of tracking capability, based on the reach of a
tracker on popular websites and apps. Our results reveal that tracker
prominence and parent-subsidiary relationships have significant impact on
accurately measuring concentration
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