Exploring rationality of self awareness in social networking for logical modeling of unintentional insiders

TL;DR

This paper investigates the rationality behind users' unintentional sharing on social networks by developing a tool that reveals publicly available information about users and studying how this affects their behavior, extending formal models of insider threats.

Contribution

It introduces a formal model of unintentional insiders within the Isabelle Insider framework and demonstrates how revealing publicly available data influences user behavior.

Findings

Revelation of public information can alter user behavior on social networks.

Unaware users can become targeted by attackers, acting as unintentional insiders.

Extended formal model captures the dynamics of unintentional insider threats.

Abstract

Unawareness of privacy risks together with approval seeking motivations make humans enter too much detail into the likes of Facebook, Twitter, and Instagram. To test whether the rationality principle applies, we construct a tool that shows to a user what is known publicly on social networking sites about her. In our experiment, we check whether this revelation changes human behaviour. To extrapolate and generalize, we use the insights gained by practical experimentation. Unaware users can become targeted by attackers. They then become unintentional insiders. We demonstrate this by extending the Isabelle Insider framework to accommodate a formal model of unintentional insiders, an open problem with long standing.