4,025 research outputs found
Privacy Issues of the W3C Geolocation API
The W3C's Geolocation API may rapidly standardize the transmission of
location information on the Web, but, in dealing with such sensitive
information, it also raises serious privacy concerns. We analyze the manner and
extent to which the current W3C Geolocation API provides mechanisms to support
privacy. We propose a privacy framework for the consideration of location
information and use it to evaluate the W3C Geolocation API, both the
specification and its use in the wild, and recommend some modifications to the
API as a result of our analysis
Horizon Report 2009
El informe anual Horizon investiga, identifica y clasifica las tecnologías emergentes que los expertos que lo elaboran prevén tendrán un impacto en la enseñanza aprendizaje, la investigación y la producción creativa en el contexto educativo de la enseñanza superior. También estudia las tendencias clave que permiten prever el uso que se hará de las mismas y los retos que ellos suponen para las aulas. Cada edición identifica seis tecnologías o prácticas. Dos cuyo uso se prevé emergerá en un futuro inmediato (un año o menos) dos que emergerán a medio plazo (en dos o tres años) y dos previstas a más largo plazo (5 años)
Web Tracking: Mechanisms, Implications, and Defenses
This articles surveys the existing literature on the methods currently used
by web services to track the user online as well as their purposes,
implications, and possible user's defenses. A significant majority of reviewed
articles and web resources are from years 2012-2014. Privacy seems to be the
Achilles' heel of today's web. Web services make continuous efforts to obtain
as much information as they can about the things we search, the sites we visit,
the people with who we contact, and the products we buy. Tracking is usually
performed for commercial purposes. We present 5 main groups of methods used for
user tracking, which are based on sessions, client storage, client cache,
fingerprinting, or yet other approaches. A special focus is placed on
mechanisms that use web caches, operational caches, and fingerprinting, as they
are usually very rich in terms of using various creative methodologies. We also
show how the users can be identified on the web and associated with their real
names, e-mail addresses, phone numbers, or even street addresses. We show why
tracking is being used and its possible implications for the users (price
discrimination, assessing financial credibility, determining insurance
coverage, government surveillance, and identity theft). For each of the
tracking methods, we present possible defenses. Apart from describing the
methods and tools used for keeping the personal data away from being tracked,
we also present several tools that were used for research purposes - their main
goal is to discover how and by which entity the users are being tracked on
their desktop computers or smartphones, provide this information to the users,
and visualize it in an accessible and easy to follow way. Finally, we present
the currently proposed future approaches to track the user and show that they
can potentially pose significant threats to the users' privacy.Comment: 29 pages, 212 reference
Case study: disclosure of indirect device fingerprinting in privacy policies
Recent developments in online tracking make it harder for
individuals to detect and block trackers. This is especially true for de-
vice fingerprinting techniques that websites use to identify and track
individual devices. Direct trackers { those that directly ask the device
for identifying information { can often be blocked with browser configu-
rations or other simple techniques. However, some sites have shifted to
indirect tracking methods, which attempt to uniquely identify a device
by asking the browser to perform a seemingly-unrelated task. One type
of indirect tracking known as Canvas fingerprinting causes the browser
to render a graphic recording rendering statistics as a unique identifier.
Even experts find it challenging to discern some indirect fingerprinting
methods. In this work, we aim to observe how indirect device fingerprint-
ing methods are disclosed in privacy policies, and consider whether the
disclosures are sufficient to enable website visitors to block the track-
ing methods. We compare these disclosures to the disclosure of direct
fingerprinting methods on the same websites.
Our case study analyzes one indirect ngerprinting technique, Canvas
fingerprinting. We use an existing automated detector of this fingerprint-
ing technique to conservatively detect its use on Alexa Top 500 websites
that cater to United States consumers, and we examine the privacy poli-
cies of the resulting 28 websites. Disclosures of indirect fingerprinting
vary in specificity. None described the specific methods with enough
granularity to know the website used Canvas fingerprinting. Conversely,
many sites did provide enough detail about usage of direct fingerprint-
ing methods to allow a website visitor to reliably detect and block those
techniques.
We conclude that indirect fingerprinting methods are often technically
difficult to detect, and are not identified with specificity in legal privacy
notices. This makes indirect fingerprinting more difficult to block, and
therefore risks disturbing the tentative armistice between individuals and
websites currently in place for direct fingerprinting. This paper illustrates
differences in fingerprinting approaches, and explains why technologists,
technology lawyers, and policymakers need to appreciate the challenges
of indirect fingerprinting.Accepted manuscrip
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