| dc.description.abstract | Online social networks (OSNs) have become an important part of people’s lives
worldwide. Although users supply OSNs with large amounts of personal data, the
ability to control the audience of one’s own information is often limited to a number
of predefined and often unclear options. In this work, we introduce two formal
frameworks, T FPPF and RT FPPF, with the aim to develop a time-sensitive
formalization of evolving OSNs and the ways information spreads in them.
Both frameworks comprise three main components. First, a social network model
is introduced to capture an OSN, together with its users, the relationships between
them, and their knowledge bases, in a specific moment in time. Then, we define the
syntax and semantics of a temporal knowledge-based logic used to reason about
knowledge and learning in sequences of social network models representing the
evolution of an OSN. Finally, we define a formal privacy policy language, powered
by the knowledge-based logic, along with a conformance relation that determines
whether a policy is violated in a specific OSN.
T FPPF and RT FPPF differ in the notion of time they use. T FPPF utilizes
the standard and temporal operators and is thus on the logic level able to
reason about time in a relative way. On the level of the privacy policy language, it
enables to write policies to be enforced in fixed time windows. On the other hand,
RT FPPF uses timestamps as a syntactic component on the logic level, allowing
for more complex formulae and privacy policies.
Both frameworks allow users to define fine-grained, time-sensitive privacy policies
based on formal logic, thus addressing the problem of privacy policy ambiguity in
OSNs. Moreover, the logic in each framework can also be used directly to reason
about knowledge in dynamic OSNs. Both frameworks constitute a step forward in
the area of OSN formalizations. | sv |
