A Probabilistic Analysis Framework for Malicious Insider Threats

Taolue  Chen; Florian Kammuller; Ibrahim  Nemli; Christian W. Probst

doi:10.1007/978-3-319-20376-8_16

A Probabilistic Analysis Framework for Malicious Insider Threats

Taolue Chen, Florian Kammuller, Ibrahim Nemli, Christian W. Probst

Department of Applied Mathematics and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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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.

Original language	English
Title of host publication	Proceedings of the third International Conference on Human Aspects of Information Security, Privacy, and Trust (HAS 2015)
Editors	Theo Tryfonas, Ioannis Askoxylakis
Publisher	Springer
Publication date	2015
Pages	178-189
ISBN (Print)	978-3-319-20375-1
ISBN (Electronic)	978-3-319-20376-8
DOIs	https://doi.org/10.1007/978-3-319-20376-8_16
Publication status	Published - 2015
Event	3rd International Conference on Human Aspects of Information Security, Privacy and Trust (HAS 2015) - Los Angeles, United States Duration: 2 Aug 2015 → 7 Aug 2015 Conference number: 3 http://2015.hci.international/has

Conference

Conference	3rd International Conference on Human Aspects of Information Security, Privacy and Trust (HAS 2015)
Number	3
Country/Territory	United States
City	Los Angeles
Period	02/08/2015 → 07/08/2015
Other	Held as Part of HCI International 2015
Internet address	http://2015.hci.international/has

Series	Lecture Notes in Computer Science
Volume	9190
ISSN	0302-9743

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20150409 Chen Kammueller Nemli Probst ProbabilisticAnalysisFrameworkAccepted author manuscript, 382 KB

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Chen, Taolue ; Kammuller, Florian ; Nemli, Ibrahim et al. / A Probabilistic Analysis Framework for Malicious Insider Threats. Proceedings of the third International Conference on Human Aspects of Information Security, Privacy, and Trust (HAS 2015). editor / Theo Tryfonas ; Ioannis Askoxylakis. Springer, 2015. pp. 178-189 (Lecture Notes in Computer Science, Vol. 9190).

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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{\textquoteright} 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.",

author = "Taolue Chen and Florian Kammuller and Ibrahim Nemli and Probst, {Christian W.}",

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booktitle = "Proceedings of the third International Conference on Human Aspects of Information Security, Privacy, and Trust (HAS 2015)",

note = "3rd International Conference on Human Aspects of Information Security, Privacy and Trust (HAS 2015), HAS ; Conference date: 02-08-2015 Through 07-08-2015",

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Chen, T, Kammuller, F, Nemli, I & Probst, CW 2015, A Probabilistic Analysis Framework for Malicious Insider Threats. in T Tryfonas & I Askoxylakis (eds), Proceedings of the third International Conference on Human Aspects of Information Security, Privacy, and Trust (HAS 2015). Springer, Lecture Notes in Computer Science, vol. 9190, pp. 178-189, 3rd International Conference on Human Aspects of Information Security, Privacy and Trust (HAS 2015), Los Angeles, United States, 02/08/2015. https://doi.org/10.1007/978-3-319-20376-8_16

A Probabilistic Analysis Framework for Malicious Insider Threats. / Chen, Taolue ; Kammuller, Florian; Nemli, Ibrahim et al.
Proceedings of the third International Conference on Human Aspects of Information Security, Privacy, and Trust (HAS 2015). ed. / Theo Tryfonas; Ioannis Askoxylakis. Springer, 2015. p. 178-189 (Lecture Notes in Computer Science, Vol. 9190).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Chen T, Kammuller F, Nemli I, Probst CW. A Probabilistic Analysis Framework for Malicious Insider Threats. In Tryfonas T, Askoxylakis I, editors, Proceedings of the third International Conference on Human Aspects of Information Security, Privacy, and Trust (HAS 2015). Springer. 2015. p. 178-189. (Lecture Notes in Computer Science, Vol. 9190). doi: 10.1007/978-3-319-20376-8_16

A Probabilistic Analysis Framework for Malicious Insider Threats

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