Clone Determiner Engine for Data Warehouse Security
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Solution Overview
Problem
Securing data cloning and sharing on data warehouses is challenging due to misrepresentation and lack of tracking integrity, as existing security measures like firewalls and CASBs are ineffective in managing cloned data assets, leading to potential data abuse issues.
Innovation Solution
A computerized system comprising a clone determiner engine that analyzes logs, timestamps, and metadata using fuzzy hashing to differentiate between primary and cloned data assets, ensuring accurate tracking and security policies can be applied.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data cloning and sharing is enabled on data warehouses, then data accessibility and collaboration are improved, but data security and integrity control deteriorate
Solution Approach 1:
The system implements continuous monitoring of data assets through log analysis and fingerprinting, creating feedback loops that detect cloning activities and trigger security responses. The clone determiner engine continuously analyzes logs and compares fingerprints to identify cloned data, enabling real-time detection and response to unauthorized cloning or sharing activities.
Solution Approach 2:
The patent introduces an intermediary security layer between data storage and access points. The clone determiner engine acts as a mediator that intercepts and analyzes data access requests, log data, and metadata before allowing operations on cloned data assets. This intermediary layer enables security control without preventing legitimate data sharing.
2Object-affected harmful factors
If traditional security measures (firewalls, CASBs) are used, then network security is maintained, but cloned data asset tracking and control become ineffective
Solution Approach 1:
The system creates cryptographic fingerprints (copies of essential data characteristics) of data assets and stores them for comparison. Instead of analyzing entire data sets, the system works with these fingerprint copies to identify cloned data assets efficiently. This copying approach enables scalable detection without the overhead of analyzing complete data volumes.
Solution Approach 2:
The patent replaces traditional mechanical/network-level security measures (firewalls, CASBs) with a data-centric approach using cryptographic fingerprinting and log analysis. This substitution transitions from perimeter-based security to content-based security, enabling detection of cloned data regardless of network location or access method.
3Measurement precision
If comprehensive log analysis and fingerprinting are performed on all data assets, then cloning detection accuracy is improved, but system complexity and processing overhead increase
Solution Approach 1:
The system extracts only the essential characteristics of data assets into fingerprints, separating the critical identification features from the complete data set. By taking out only the necessary fingerprint information and log metadata needed for clone detection, the system achieves high detection accuracy without processing entire data volumes, reducing complexity while maintaining precision.
Data Source
AI summary
In one aspect, a computerized system for securing data cloning and sharing options on data warehouses, comprising: a clone determiner engine that determines that a data asset is a primary data asset or a clone data asset, wherein the clone determiner engine comprises: a log data analyzer that obtains and analyzes a set of logs of the data asset from a specified log source, and wherein set of logs are used to determine that the data asset is the primary data asset or the clone data asset, a timestamp analyzer engine that obtains a timestamp data of the data asset and reviews the timestamp data to analyze ordering of the data asset, and wherein the timestamp analyzer engine determines the data asset is a primary asset or a secondary asset, and a fingerprints analyzer that obtains and reviews the data asset and any metadata of data asset, and wherein the fingerprints analyzer creates a fingerprint based on a content of the data asset and the metadata of the data asset, and wherein the fingerprints analyzer then uses the fingerprints to determine that the data asset is the clone data asset of an already known asset in conjunction with an output of the timestamp analyzer engine and the log data analyzer.


