Centralized Data Protection Hub for Secure Migration
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Solution Overview
Problem
Current data security implementations across different organizations are fragmented, leading to inefficiencies in data flow, increased costs, and potential compliance issues due to varying levels of expertise and differing security standards, which can expose data to compromise.
Innovation Solution
A data protection hub system that receives unprotected data and policy parameters, applies appropriate data protection transformations such as encryption, hashing, or tokenization, and sends protected data, ensuring compliance with industry standards and facilitating secure data migration between applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If each organization implements independent data security solutions, then each organization can meet its specific security needs, but the complexity and cost of implementation increases significantly
Solution Approach 1:
The patent consolidates multiple independent data security implementations into a single centralized data protection hub that serves multiple organizations. This hub provides unified data security services, reducing the overall complexity while maintaining the ability to meet diverse security requirements through a shared infrastructure
Solution Approach 2:
The data protection hub is designed as a universal system that can serve multiple organizations with different security needs through a single multi-functional platform. It provides data security services to various clients without requiring separate implementations, thereby reducing complexity while maintaining reliability
2Reliability
If each organization implements independent data security solutions, then each organization can address its specific requirements, but the cost of implementation increases
Solution Approach 1:
By merging multiple independent security implementations into a single shared data protection hub, the patent enables cost savings through resource consolidation. Multiple organizations share the same security infrastructure, reducing duplicate investments in hardware, software, and expertise while maintaining adequate security coverage
Solution Approach 2:
The universal data protection hub serves multiple organizations through a single platform, reducing the total cost of implementation. Instead of each organization bearing the full cost of independent security solutions, they share the costs of a multi-functional system that addresses their collective security needs
3Adaptability or versatility
If different organizations implement varying data security solutions, then each can adapt to its needs, but data flow between organizations is inhibited
Solution Approach 1:
The data protection hub acts as an intermediary between multiple organizations, enabling secure data flow while maintaining the ability to customize security measures. Data can flow through this central mediator that applies appropriate security transformations based on policy parameters, thus maintaining both adaptability and productivity
4Ease of operation
If organizations with varying expertise implement data security independently, then each can make decisions autonomously, but compliance with industry standards may be compromised
Solution Approach 1:
The data protection hub incorporates feedback mechanisms that ensure compliance with industry standards while allowing autonomous operation. Policy parameters and compliance requirements are fed into the system, and the hub automatically adjusts its security measures to meet these standards, providing both autonomy and compliance assurance
Data Source
AI summary
Embodiments of the invention broadly described, introduce systems and methods for protecting data at a data protection hub using a data protection policy. One embodiment of the invention discloses a method for protecting unprotected data. The method comprises receiving a data protection request message comprising unprotected data and one or more policy parameters, determining a data protection transformation using the policy parameters, performing the data protection transformation on the unprotected data to generate protected data, and sending the protected data.