Aggregate Classification for Data Collection Policy Enforcement
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Solution Overview
Problem
Conventional classification-based data management systems face limitations when handling collections of information assets with differing classifications, as they are defined based on individual asset classifications rather than aggregate characteristics, leading to inefficient policy enforcement.
Innovation Solution
A computer-implemented method and system for aggregating information-asset classifications, which identifies a data collection, derives an aggregate classification based on the classifications of included assets, and associates this classification with the collection to enforce data management policies, using methods such as union, maximum, average, or minimum classification values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional classification-based data management policies are used, then individual asset classifications can be enforced, but collections of assets with differing classifications cannot be managed efficiently
Solution Approach 1:
The patent merges individual asset classifications into a single aggregate classification at the collection level. The system combines multiple classifications (e.g., public, internal, confidential) into one unified classification that represents the entire collection, enabling simplified policy enforcement while maintaining adaptability to diverse asset types.
Solution Approach 2:
The aggregate classification system provides universal applicability by creating a single policy definition that can manage collections containing assets with different classifications. This multi-functional approach allows one policy to handle multiple classification scenarios simultaneously, reducing the need for separate policies for each asset type.
2Productivity
If policies are defined based on individual asset classifications, then precise control over each asset is achieved, but policy enforcement becomes inefficient for collections
Solution Approach 1:
The system performs preliminary aggregation of classifications at the collection level before policy enforcement. By pre-computing the aggregate classification that represents all assets in a collection, the system eliminates the need for time-consuming independent scanning and classification of each asset during policy enforcement operations.
Solution Approach 2:
The patent creates a representative copy of the collection's classification characteristics through the aggregate classification. This copy encapsulates the essential classification information of all assets in the collection, allowing policy enforcement to operate on the simplified representation rather than processing each individual asset, thereby significantly improving efficiency.
3Reliability
If aggregate classification is derived using union of classifications, then comprehensive coverage is achieved, but classification precision may be reduced
Solution Approach 1:
The system changes the parameter of classification from individual asset level to collection level aggregation. By transitioning from fine-grained individual classifications to coarse-grained aggregate classifications, the system maintains reliability for policy enforcement while accepting reduced precision at the individual asset level in exchange for improved operational efficiency and simplified management.
Data Source
AI summary
The disclosed computer-implemented method for aggregating information-asset classifications may include (1) identifying a data collection that includes two or more information assets, (2) identifying a classification for each of the information assets, (3) deriving, based at least in part on the classifications of the information assets, an aggregate classification for the data collection, and (4) associating the aggregate classification with the data collection to enable a data management system to enforce a data management policy based on the aggregate classification. Various other methods, systems, and computer-readable media are also disclosed.


