Wirtschaftsuniversität Wien Magisterarbeit - SemanticLab

collect a lot of personal data about people by indexing several websites and hence make
this sensitive data available to anyone with one click by entering a simple query into the
search engine - security through obscurity is not existent anymore if personal data has
been published on the Internet [Pik2006]. This problem area especially arises when it
comes to social networks which the following section is going to deal with.
2.3.4. Social networks
Social networks such as Facebook, LinkedIn, MySpace or StudiVZ are getting more
popular every day, hence attract more users and collect more data [Gro05]. One principle
of such platforms is that users have to register to create a profile. There they can enter
all kind of personal data: Name, address, contact information such as e-mail or telephone
number, date of birth, hobbies, photos, relationship status, employer and so on. If users
want to, they are literally able to publish their whole curriculum vitae. One of the main
reasons to join such a social network is to get connected to friends and other people
by “adding” them as “friends”. With this feature, social networks can be calculated
by the provider of the platform: friends of friends are suggested to other users because
they may know them, live near them or attended the same class, different connections
to other friends can be displayed and so on. All this leads to a huge threat to privacy
if not necessary mechanisms are in place to make sure that all this very sensitive user
data is not mis-used (e.g. for data mining), sold (e.g. to direct marketing companies) or
stolen (and then, for example, used for identity theft). Although all such platforms offer
privacy settings, the default settings are not very strict. The reason for this was already
mentioned earlier: there is a trade-off between privacy and functionality, especially for
social networks. In addition to that, every information about its users is an asset for
the platform operators. [Gro05] discusses privacy implications of social networks based
on the example of Facebook which are broken down into the following categories:
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• Stalking: As user profiles often not only include information about the residence
but also about the occupation (such as the university and currently attended classes
at university), stalkers can easily identify the physical location during the day. Especially
status messages can also reveal information which could be used to locate
the physical location of users. Besides physical stalking, potential adversaries could
stalk their victim via instant messaging (IM) as IM account-names are very often
provided in user profiles.
• Re-identification: Besides using data such as date of birth and zip-codes, users
can easily be identified via posted pictures. Depending on the country, available
data on social networks can also easily be used for identity theft. The social
security number in the US, for example, can almost be estimated if the following
information is available: date of birth, hometown and current residence - all this
information is often present in user profiles [Gro05].
• Building a digital dossier: By collecting data about users, a digital dossier can
easily be build, especially over time. Changing home-towns, partnership details,