Distributed Data Security via Encrypted Sector Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage systems face challenges with limited storage capacity and compute power in local devices, bandwidth limitations in cloud storage, and the need for secure data management in distributed edge applications, particularly in scenarios like surveillance systems where data security and integrity are critical.
Innovation Solution
The method involves partitioning data chunks into sectors, encrypting them with different random keys, and encoding these keys with channel codes, then appending them to the encrypted sectors for secure storage across multiple distributed store units, ensuring that even if one portion is decrypted, the other remains inaccessible to malicious entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in distributed store units with encryption, then data security is improved, but device complexity increases due to key management and encoding requirements
Solution Approach 1:
The data is divided into multiple sectors that are distributed across different store units. Each sector is encrypted with a unique random key, and the keys are encoded with channel codes before being appended to their corresponding encrypted sectors. This segmentation approach enhances security by ensuring that compromise of one store unit does not affect others, while the systematic structure of segmentation manages the complexity through standardized procedures.
Solution Approach 2:
Channel codes are introduced as an intermediary layer between the random encryption keys and their storage. The channel codes provide error correction and additional security mechanisms, mediating the complexity of direct key storage while enhancing overall system reliability. This intermediary layer simplifies key management by adding robustness without requiring complex custom error handling procedures.
2Reliability
If data is partitioned and distributed across multiple store units, then data security is improved, but storage capacity requirements increase
Solution Approach 1:
The original data is partitioned into multiple sectors that are distributed across different store units. Each sector contains a portion of the encrypted data along with its corresponding encoded random key. This segmentation provides security through distribution while the efficient encoding of keys minimizes the additional storage overhead, balancing security requirements with storage capacity constraints.
3Reliability
If channel codes are used to encode random keys, then error correction and security are improved, but processing time increases
Solution Approach 1:
The random keys are encoded with channel codes during the initial data storage phase, before any potential data retrieval or error conditions occur. This preliminary encoding establishes error correction capability in advance, so that during retrieval, the system can quickly decode and verify keys without experiencing delays from error detection and correction during critical access operations.
Data Source
AI summary
A method includes partitioning a received data chunk into first and second data sectors to be stored in respective first and second store units. The method also includes generating first and second random keys. The method further includes encrypting the first data sector with the second random key, and encrypting the second data sector with the first random key. The first and second random keys are encoded with channel codes. Thereafter, the first encoded random key is appended to the first encrypted data sector to obtain first appended data, and the second encoded random key is appended to the second encrypted data sector to obtain second appended data.