GPT-Based Data Security System with Local Key Encryption
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Solution Overview
Problem
Conventional data security systems face challenges in ensuring secure data transfer between storage locations, as they often rely on encryption/decryption methods that require destination applications to decrypt data, which can lead to security breaches due to vulnerabilities at destination storage locations.
Innovation Solution
An Information Handling System (IHS) that utilizes a Globally Unique Identifier (GUID) Partition Table (GPT) to manage data security by determining whether a server device satisfies security requirements identified in a security tag, and only transfers data if those requirements are met, employing network and local security keys to secure data across multiple storage locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional encryption/decryption methods are used for data transfer, then data can be accessed at destination storage locations, but security breaches occur due to vulnerabilities at destination storage locations
Solution Approach 1:
Instead of encrypting data before storage and decrypting at retrieval (conventional approach), the patent inverts the approach by encrypting data in-place at the storage location using local security keys stored in secure elements within the storage device itself. This eliminates the need for data to be decrypted at destination, maintaining security while enabling accessibility.
Solution Approach 2:
The patent introduces secure elements (trusted platform modules or secure processors) as intermediaries within the storage device that hold security keys and perform encryption/decryption operations locally. This intermediary layer prevents direct access to plaintext data even when the storage device is accessed, resolving the contradiction between accessibility and security.
2Reliability
If the same level of security is applied to all storage devices, then data security is maintained across locations, but cost and complexity increase significantly
Solution Approach 1:
The patent applies local quality by implementing security features specifically at the storage device level through integrated secure elements, rather than requiring complex centralized security infrastructure at all locations. Each storage device independently maintains its security through local keys and encryption, achieving consistent security without uniform high complexity across the entire system.
Solution Approach 2:
The storage devices perform self-service security operations by locally storing security keys in secure elements and performing encryption/decryption autonomously without requiring external key management infrastructure. This self-service approach maintains security consistency across distributed locations while reducing overall system complexity.
Data Source
AI summary
A GPT-based multi-location data security system includes a first server device coupled to a second server device through a network. The first server device includes a storage device that includes a GPT that identifies a data storage partition on the storage device that stores data, and that includes a security tag that identifies security requirements for the data stored on the data storage partition. A multi-location data security subsystem in the first server device is coupled to the storage device. The multi-location data security subsystem receives a request to transfer the data stored on the data storage partition to the second server device, and determines whether the second server device satisfies the security requirements for the data stored on the data storage partition. If the second server device satisfies the security requirements identified in the security tag, the first server device transfer the data to the second server device.