Provenance-Aware Data Filtering for Compliant Transfer and Storage
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Solution Overview
Problem
Inconsistent application of data security rules across different entities leads to conflicts and inefficiencies in preventing illicit data transfer and storage, burdening developers with manual rule-processing and maintenance, which can result in unintentional breaches.
Innovation Solution
A computing platform that retrieves data items and their provenance records, applies relevant rules based on call context, and evaluates data items/properties to determine compliance, setting status codes for permitted transfers or storage, and removing prohibited content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If different entities implement their own data security rules, then each entity can enforce its specific security requirements, but the inconsistent application of rules across entities creates complexity and potential breaches
Solution Approach 1:
The patent introduces a centralized rule service as an intermediary that mediates between data requests and storage systems. This service receives data requests, evaluates them against consolidated security rules, and enforces compliance centrally, eliminating the need for each entity to independently implement and manage their own rule sets while maintaining reliable security enforcement
Solution Approach 2:
The centralized rule service performs multiple functions: it consolidates rules from different entities, evaluates data requests against these rules, determines compliance, and enforces security policies. This universal service replaces multiple separate rule implementation systems, reducing overall complexity while maintaining comprehensive security coverage
2Reliability
If developers manually process and maintain data security rules, then specific security requirements can be enforced, but the manual efforts increase workload and can lead to unintentional breaches
Solution Approach 1:
The system enables automated self-service where the centralized rule service automatically receives data requests, retrieves applicable security rules, evaluates compliance, and enforces policies without requiring developer intervention. This automation eliminates manual rule processing and maintenance while ensuring consistent security compliance
Solution Approach 2:
The system performs preliminary actions by pre-consolidating security rules from multiple entities into a centralized repository before data requests occur. When data requests are made, the evaluation against pre-consolidated rules happens automatically, eliminating the need for developers to manually process rules at the time of data operations
Data Source
AI summary
Examples of the present disclosure describe systems and methods for preventing illicit data transfer and storage. In aspects, a computing platform may receive a data request from a caller system, device, or service. The computing platform may identify data items/properties associated with the data request and retrieve one or more rules relevant to the caller and/or caller location. The retrieved rule(s) may be used to evaluate the data item(s) such that data items, data item content, and/or data item properties that are prohibited by the retrieved rule(s) from being manipulated (e.g., accessed, transferred, stored) are removed from the identified data item(s). Based on the evaluation of the identified data item(s), one or more relevant status codes may be set. The computing platform may then manipulate the identified data item(s) in accordance with the data request and provide a processing response to the caller.