Secure Data Analytics via Edge Tokenization
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Solution Overview
Problem
Conventional systems fail to securely access and perform analytics on data stored on multiple independent computing devices, exposing data to vulnerabilities when transferred to cloud environments.
Innovation Solution
A secure siloed analytics system that connects with entity and computing device systems, uses an artificial intelligence engine to perform analytics, tokenizes data based on hardware identification, and transfers insights securely without relying on cloud storage, enabling on-the-go analytics and instant data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is transferred to cloud environments for storage and analytics, then accessibility and processing capability are improved, but data security and vulnerability exposure worsen
Solution Approach 1:
The patent introduces a secure analytics system as an intermediary between data sources and analytics processing. This system performs analytics locally on connected devices without requiring cloud transfer, acting as a mediator that eliminates the vulnerable cloud storage step while maintaining analytics capability.
Solution Approach 2:
The patent extracts the analytics processing function from cloud-dependent architectures and implements it locally on edge devices. By taking out the analytics capability from the cloud environment and placing it directly on devices with data, the system eliminates cloud storage vulnerabilities while preserving data accessibility and processing.
2Power
If conventional systems use cloud storage for data analytics, then processing power is improved, but data protection and security control deteriorate
Solution Approach 1:
The patent shifts the analytics processing from a centralized cloud dimension to a distributed edge computing dimension. By performing analytics locally on multiple connected devices rather than centralizing in the cloud, the system maintains processing power across distributed nodes while improving data protection through localized processing.
Solution Approach 2:
The patent segments the analytics processing across multiple independent devices rather than relying on a single cloud infrastructure. Each device performs analytics on its local data, dividing the processing power across segments while maintaining data protection through distributed architecture.
3Ease of operation
If data is stored in centralized cloud environments, then data accessibility is improved, but system security and data sovereignty worsen
Solution Approach 1:
The patent implements local quality by performing analytics and processing data locally on connected devices rather than centrally in the cloud. Each device maintains sovereignty over its data while providing local analytics capability, eliminating the need to surrender data sovereignty to centralized cloud storage.
Data Source
AI summary
Embodiments of the present invention provide a system for securing and allowing access to electronic data in a data storage container. The system is configured for identifying initiation of a connection with an data storage container, determining establishment of the connection with the data storage container, instantaneously crawling into the data storage container to access data that is associated with the data storage container, instantaneously performing one or more operations associated with the data, storing information associated with the one or more operations in a data store, identifying initiation of a connection with an entity system, determining establishment of the connection with the entity system, instantaneously transferring the information associated with the one or more operations to the entity system, and performing one or more actions, via one or more applications stored on the entity system, utilizing the information associated with the one or more operations.