Baracaldo, N and Joshi, J
(2012)
A trust-and-risk aware RBAC framework: Tackling insider threat.
In: UNSPECIFIED.
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Abstract
Insider Attacks are one of the most dangerous threats organizations face today. An insider attack occurs when a person authorized to perform certain actions in an organization decides to abuse the trust, and harm the organization. These attacks may negatively impact the reputation of the organization, its productivity, and may produce losses in revenue and clients. Avoiding insider attacks is a daunting task. While it is necessary to provide privileges to employees so they can perform their jobs efficiently, providing too many privileges may backfire when users accidentally or intentionally abuse their privileges. Hence, finding a middle ground, where the necessary privileges are provided and malicious usage are avoided, is necessary. In this paper, we propose a framework that extends the role-based access control (RBAC) model by incorporating a risk assessment process, and the trust the system has on its users. Our framework adapts to suspicious changes in users' behavior by removing privileges when users' trust falls below a certain threshold. This threshold is computed based on a risk assessment process that includes the risk due to inference of unauthorized information. We use a Coloured-Petri net to detect inferences. We also redefine the existing role activation problem, and propose an algorithm that reduces the risk exposure. We present experimental evaluation to validate our work. Copyright 2012 ACM.
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Details
| Item Type: |
Conference or Workshop Item
(UNSPECIFIED)
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| Status: |
Published |
| Creators/Authors: |
|
| Date: |
25 July 2012 |
| Date Type: |
Publication |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Journal or Publication Title: |
Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT |
| Page Range: |
167 - 176 |
| Event Type: |
Conference |
| DOI or Unique Handle: |
10.1145/2295136.2295168 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Information Sciences > Information Science |
| Refereed: |
Yes |
| ISBN: |
9781450312950 |
| Date Deposited: |
08 Aug 2012 15:42 |
| Last Modified: |
01 May 2020 12:55 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/13459 |
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