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SACMAT
2011
ACM

Modeling data flow in socio-information networks: a risk estimation approach

7 years 9 months ago
Modeling data flow in socio-information networks: a risk estimation approach
Information leakage via the networks formed by subjects (e.g., Facebook, Twitter) and objects (e.g., blogosphere) − some of whom may be controlled by malicious insiders − often leads to unpredicted access control risks. While it may be impossible to precisely quantify information flows between two entities (e.g., two friends in a social network), this paper presents a first attempt towards leveraging recent advances in modeling socio-information networks to develop a statistical risk estimation paradigm for quantifying such insider threats. In the context of socio-information networks, our models estimate the following likelihoods: prior flow − has a subject s acquired covert access to object o via the networks? posterior flow − if s is granted access to o, what is its impact on information flows between subject s′ and object o′ ? network evolution − how will a newly created social relationship between s and s′ influence current risk estimates? Our goal is not to...
Ting Wang, Mudhakar Srivatsa, Dakshi Agrawal, Ling
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SACMAT
Authors Ting Wang, Mudhakar Srivatsa, Dakshi Agrawal, Ling Liu
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