Cloud Device Registration Using QR Codes and Intermediate Storage
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Solution Overview
Problem
Existing cloud-based management service registration methods for computing devices face limitations in data capacity and reliability due to noise in matrix barcodes, such as QR codes, which can lead to failed data replication and increased complexity, time, and resource consumption.
Innovation Solution
The use of an intermediate cloud storage system to decrypt and manage encrypted data blobs, utilizing session identifiers, decryption keys, and correlation keys through QR codes, allowing secure and efficient registration of user devices with cloud-based management services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If data blob is extracted by reading matrix barcode (QR code), then registration process is automated, but data capacity is limited by reader capabilities and noise may cause replication failure
Solution Approach 1:
The data blob is segmented into two parts: essential identification data is encoded in the QR code for automated extraction, while additional data is stored separately in the data blob file. This segmentation allows the QR code to remain compact and noise-resistant while the full data can be retrieved from the data blob, resolving the contradiction between automation and reliability.
Solution Approach 2:
The patent introduces an intermediary verification process where the extracted QR code data is used to retrieve and verify the complete data blob. This intermediary step ensures that even if the QR code contains noise, the registration can proceed by verifying against the stored data blob, thus maintaining reliability while preserving automation.
2Quantity of substance
If QR code resolution is increased to store more data, then data capacity increases, but noise impact increases and replication may fail
Solution Approach 1:
The patent extracts only the essential identification data into the QR code, leaving the remaining data to be stored in the data blob file. This extraction resolves the contradiction by keeping the QR code compact and noise-resistant while still providing sufficient identification information to retrieve the full data set from the data blob.
Solution Approach 2:
The data blob is prepared and stored in advance with all necessary registration information, while the QR code contains only a reference or essential identifier. This preliminary action ensures that the full data is already available and verified before registration, eliminating the need to rely on high-capacity QR codes and their associated noise problems.
3Reliability
If manual data blob collection and upload is performed, then data security is maintained, but administrative time and resource consumption increase
Solution Approach 1:
The device automatically performs the data blob collection and upload process itself after the QR code is scanned. The system self-services by retrieving the pre-stored data blob and submitting it for registration without requiring administrator intervention, thus maintaining security through controlled access while dramatically reducing the time and resources required compared to manual processes.
Data Source
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AI summary
Techniques are described herein that are capable of registering a user device with a cloud-based management service using an intermediate cloud storage. For instance, the intermediate cloud storage may store an encrypted data blob including information that identifies the user device. The intermediate cloud storage or a registration system may decrypt the encrypted data blob so that the registration system may use the decrypted data blob to register the user device with the cloud-based management service. For instance, the registration system may retrieve the encrypted or decrypted data blob from the intermediate cloud storage by providing a requisite secret to the intermediate cloud storage. The requisite secret may be provided to the registration system by the user device (e.g., via a matrix barcode, such as a QR code).