Admonita: A recommendation-based trust model for dynamic data integrity
Document Type
Conference Proceeding
Publication Date
2021
Department
Department of Computer Science
Abstract
Data integrity is critical to the secure operation of a computer system. Applications need to know that the data that they access is trustworthy. Many current production-level integrity models are tightly coupled to a specific domain, (e.g., databases), or only apply after the fact (e.g., backups). In this paper we propose a recommendation-based trust model, called Admonita, for data integrity that is applicable to any structured data in a system and provides a measure of trust to applications on-the-fly. The proposed model is based on the Biba integrity model and utilizes the concept of an Integrity Verification Procedure (IVP) proposed by Clark-Wilson. Admonita incorporates subjective logic to maintain the trustworthiness of data and applications in a system. To prevent critical applications from losing trust, Admonita also incorporates the principle of weak tranquility to ensure that highly trusted applications can maintain their trust levels. We develop a simple algebra around these elements and describe how it can be used to calculate the trustworthiness of system entities. By applying subjective logic, we build a powerful, artificial and reasoning trust model for implementing data integrity.
Publication Title
ICISSP 2021 - Proceedings of the 7th International Conference on Information Systems Security and Privacy
ISBN
9789897584916
Recommended Citation
Al-Mawee, W.,
Carr, S.,
&
Mayo, J.
(2021).
Admonita: A recommendation-based trust model for dynamic data integrity.
ICISSP 2021 - Proceedings of the 7th International Conference on Information Systems Security and Privacy,
1, 273-282.
http://doi.org/10.5220/0010150402730282
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/14737
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.