Secure Data Access via Local-Remote Query Segmentation
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Solution Overview
Problem
Cloud computing systems face security challenges due to the vulnerability of sensitive data stored on remote computer systems, as users lose control over data stored in third-party locations and face potential security breaches during transmission over the Internet.
Innovation Solution
A method that transforms queries to separately access and process data stored on both local and remote computer systems, where sensitive data is stored locally and less sensitive data is stored remotely, ensuring secure access by incorporating data elements from the remote system into local queries for comprehensive data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored on remote computer systems (cloud), then accessibility and scalability are improved, but security and control are worsened
Solution Approach 1:
The patent segments data into two categories: sensitive data stored locally on the user's computer system and non-sensitive data stored remotely on cloud computer systems. This segmentation allows the system to maintain security for critical information while still benefiting from cloud accessibility and scalability for less sensitive data.
Solution Approach 2:
The patent introduces a gateway component that acts as an intermediary between the local computer system and remote cloud systems. This gateway manages data transmission, enforces security policies, and coordinates queries across both local and remote data sources, enabling secure cloud integration without compromising local data protection.
2Ease of operation
If sensitive data is transmitted over the Internet to remote systems, then accessibility is improved, but vulnerability to security breaches increases
Solution Approach 1:
The patent extracts sensitive data elements from the data set and retains them exclusively on the local computer system, preventing their transmission over the Internet. Only non-sensitive data elements are transmitted to and accessed from remote cloud systems, thereby eliminating the security breach risk associated with transmitting sensitive information while maintaining cloud accessibility for appropriate data.
Solution Approach 2:
The patent implements preliminary security measures by identifying and classifying sensitive data elements before any transmission occurs. The system proactively prevents sensitive data from being sent to remote systems by maintaining local copies and using only non-sensitive data for cloud operations, thus preventing potential security breaches before they can occur.
3Reliability
If data is stored locally to maintain security, then control and security are improved, but accessibility and scalability are worsened
Solution Approach 1:
The patent segments the data storage architecture into local and remote components, with sensitive data stored locally for security control and non-sensitive data stored remotely for scalability. This hybrid segmentation enables the system to achieve both security control and scalability by appropriately distributing different types of data across different storage locations.
Solution Approach 2:
The patent creates a universal data access architecture that can handle both local and remote data sources through a unified query interface. The gateway component provides multi-functionality by supporting local file access, remote cloud access, and coordinated queries across both, enabling the system to scale while maintaining security control.
4Reliability
If a hybrid local-remote storage system is implemented, then security is improved, but system complexity increases
Solution Approach 1:
The patent introduces a gateway component as an intermediary that manages the complexity of the hybrid local-remote storage system. This gateway handles query routing, data classification, and coordination between local and remote systems, centralizing the management of complexity and shielding users from the underlying system architecture complexity while maintaining security.
Solution Approach 2:
The patent implements automated data classification and routing mechanisms that enable the system to self-manage the hybrid architecture. The gateway automatically identifies sensitive versus non-sensitive data, routes queries to appropriate storage locations, and manages data transmission protocols, reducing the operational complexity burden on users while maintaining security.
Data Source
AI summary
In one embodiment the present invention includes a computer-implemented method comprising receiving a first query in a local computer system to access data stored on a remote computer system the local computer system. Data elements of the remote data are associated with data elements of the local data. The query is transformed into multiple queries. A second query is sent to the remote computer system to retrieve remote data. A first data result is received and stored on the local computer system and incorporated into a third query. The third query is executed against the local data and the first data result to produce a result. Sensitive data may be stored locally in a dimension table of a star schema and non-sensitive data may be stored remotely in a fact table and another dimension table of the star schema, for example.