4 research outputs found
Model Checking Social Network Models
A social network service is a platform to build social relations among people
sharing similar interests and activities. The underlying structure of a social
networks service is the social graph, where nodes represent users and the arcs
represent the users' social links and other kind of connections. One important
concern in social networks is privacy: what others are (not) allowed to know
about us. The "logic of knowledge" (epistemic logic) is thus a good formalism
to define, and reason about, privacy policies. In this paper we consider the
problem of verifying knowledge properties over social network models (SNMs),
that is social graphs enriched with knowledge bases containing the information
that the users know. More concretely, our contributions are: i) We prove that
the model checking problem for epistemic properties over SNMs is decidable; ii)
We prove that a number of properties of knowledge that are sound w.r.t. Kripke
models are also sound w.r.t. SNMs; iii) We give a satisfaction-preserving
encoding of SNMs into canonical Kripke models, and we also characterise which
Kripke models may be translated into SNMs; iv) We show that, for SNMs, the
model checking problem is cheaper than the one based on standard Kripke models.
Finally, we have developed a proof-of-concept implementation of the
model-checking algorithm for SNMs.Comment: In Proceedings GandALF 2017, arXiv:1709.0176
Detecting bots with temporal logic
Social bots are computer programs that act like human users on social media platforms. Social bot detection is a rapidly growing field dominated by machine learning approaches. In this paper, we propose a complementary method to machine learning by exploring bot detection as a model checking problem. We introduce Temporal Network Logic (TNL) which we use to specify social networks where agents can post and follow each other. Using this logic, we formalize different types of social bot behavior with formulas that are satisfied in a model of a network with bots. We also consider an extension of the logic where we explore the expressive power of including elements from hybrid logic in our framework. We give model checking algorithms for TNL and its hybrid extension, and show that the complexity of the former is in P and the latter in PSPACE.publishedVersio