Conference paper · Book chapter
A Probabilistic Analysis Framework for Malicious Insider Threats
In
Lecture Notes in Computer Science
—
2015, pp. 178-189
Abstract
Malicious insider threats are difficult to detect and to mitigate. Many approaches for explaining behaviour exist, but there is little work to relate them to formal approaches to insider threat detection. In this work we present a general formal framework to perform analysis for malicious insider threats, based on probabilistic modelling, verification, and synthesis techniques.
The framework first identifies insiders’ intention to perform an inside attack, using Bayesian networks, and in a second phase computes the probability of success for an inside attack by this actor, using probabilistic model checking.
| Language: | English |
|---|---|
| Publisher: | Springer |
| Year: | 2015 |
| Pages: | 178-189 |
| Proceedings: | 3rd International Conference on Human Aspects of Information Security, Privacy and Trust (HAS 2015) |
| Series: | Lecture Notes in Computer Science |
| ISBN: | 3319203754 , 3319203762 , 9783319203751 and 9783319203768 |
| ISSN: | 03029743 and 16113349 |
| Types: | Conference paper and Book chapter |
| DOI: | 10.1007/978-3-319-20376-8_16 |
| ORCIDs: | Probst, Christian W. |
