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US 11,886,397 B2Granted
Multi-faceted trust system
AssigneeASG Technologies Group, Inc.
InventorsJean-Philippe Moresmau, Marcus MacNeill
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AssigneeASG Technologies Group, Inc.
InventorsJean-Philippe Moresmau, Marcus MacNeill
Estimating the term…
Provided are methods and systems for determining multi-faceted trust scores for data. A method may commence with receiving data and determining a plurality of metadata items associated with the data. The method may continue with determining one or more facets associated with each of the plurality of metadata items. The method may further include determining a parameter and a weight associated with each of the one or more facets. Upon determining the parameter and the weight, a trust score associated with each of the plurality of metadata items may be calculated based on the parameter and the weight associated with each of the one or more facets. The method may further include calculating a multi-faceted trust score of the data based on the trust score of each of the plurality of metadata items.
A method for determining multi-faceted trust scores for computer network data, the method comprising:
A system for determining multi-faceted trust scores for computer network data, the system comprising:
A system for determining multi-faceted trust scores for computer network data, the system comprising:
Dependencies are inferred from the claim text.
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Design, administration or maintenance of databases: improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or…
With adaptation to user needs: using data annotations, e.g. user-defined metadata
Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates…:…
Protecting access to data via a platform, e.g. using keys or access control rules: to a system of files or objects, e.g. local or distributed file…
About 13 years 5 months of term left · ends 4 Apr 2040 (estimated)
This application relates generally to data processing and, more specifically, to systems and methods for determining multi-faceted trust scores for data.
Defensive data strategies, such as regulatory compliance, require a truth-based approach to understanding data that is both highly automated and accurate. Instituting the same approach for offensive data strategies, such as self-service data analytics, would be costly, time consuming, and even impossible in some situations (for example, when combining internal and external data).
This summary is provided to introduce a selection of concepts in a simplified form that are further described in the Detailed Description below. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
Exemplary embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements.
FIG. 1 illustrates an environment within which methods and systems for determining multi-faceted trust scores for data can be implemented, according to an example embodiment.
FIG. 2 is a block diagram illustrating a system for determining multi-faceted trust scores for data, according to an example embodiment.
The following detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show illustrations in accordance with exemplary embodiments. These exemplary embodiments, which are also referred to herein as “examples,” are described in enough detail to enable those skilled in the art to practice the present subject matter. The embodiments can be combined, and other embodiments can be formed, by introducing structural and logical changes without departing from the scope of what is claimed. The following detailed description is, therefore, not to be taken in a limiting sense and the scope is defined by the appended claims and their equivalents.
In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one. In this document, the term “or” is used to refer to a nonexclusive “or,” such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. Furthermore, all publications, patents, and patent documents referred to in this document are incorporated by reference herein in their entirety, as though individually incorporated by reference. In the event of inconsistent usages between this document and those documents so incorporated by reference, the usage in the incorporated reference(s) should be considered supplementary to that of this document; for irreconcilable inconsistencies, the usage in this document controls.
The present disclosure relates to systems and methods for determining multi-faceted trust scores for data. The system of the present disclosure provides an approach for understanding data in support of offensive data strategies that include augmenting truth (where available) with a dynamic trust model comprised of multiple facets. The system of the present disclosure can be used to analyze critical data components or other data items and determine a degree to which the data can be trusted by the users. The trust score can be calculated based on several factors, which are referred to herein as facets. More specifically, each of the facets includes a characteristic of a metadata item of data. The trust score is also referred to as a “score” herein.