Authors:
Wassnaa Al-Mawee
1
;
Steve Carr
1
and
Jean Mayo
2
Affiliations:
1
Department of Computer Science, Western Michigan University, 1903 W. Michigan Ave., Kalamazoo, MI 49008-5466, U.S.A.
;
2
Department of Computer Science, Michigan Technological University, 1400 Townsend Dr., Hougton, MI 49931-1292, U.S.A.
Keyword(s):
Data Integrity, Biba Model, Trust, Subjective Logic, Tranquility.
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
th
ese 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.
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