Every day, today’s information society challenges individuals in dealing with the availability of a large and growing amount of information. At the same time, a variety of personal data of individuals is collected, processed, stored and eventually used by public bodies, non-profit organisations, and commercial organisations. The sum of the personal data about an individual denotes its (digital) identity. Subsets of this identity (referred to as partial identity) are disclosed when using and interacting with services via the internet (cp. Fig 1). Such personal data constituting a digital identity may include explicit information, which was consciously disclosed (e.g. in social networks), personal data assigned by third parties (e.g. telephone number, car plate, etc.) and implicit information collected by observing the behavior of individuals (e.g. personal preferences, credit rating).
Fig. 1: Model of partial identities (Source: www.fidis.net)
The objective of the master thesis is to provide an overview of personal data being collected and processed by organisations. This comprises the exploration of the possibilities to expand organisation’s knowledge about individuals by using profiling techniques, such as: …
• … deriving further information about individuals from the existing personal data (e.g. estimation of income based on education)
• … cross-referencing collected personal data with external statistical data (e.g. credit worthiness based on place of residence)
• … linking existing partial identities in order to get access to additional personal data about an individual (e.g. linking private and business information about an individual)
Finally, it should be discussed which amount of this complete set of information is necessary for organisations to:
a) … offer a service
b) … raise the quality and user experience of a service
c) … respond to business model needs of an advertisement based revenue model
Eventually, this allows the thesis to conclude on the collected personal data about individuals in relation to the received benefits in exchange (cp. Fig 2).
The planed results of this thesis constitute a further step towards making the tradeoff between personal data disclosure and received benefits from service providers more transparent to individuals, allowing them to make more informed decision regarding their privacy (protection).
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Teaching
