Encrypted Data Search via Fixed Shuffle and Segmentation
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Solution Overview
Problem
Conventional encryption methods require decryption of large datasets for programmatic search, making it time- and resource-intensive, and storing data in unencrypted form for cloud systems compromises security.
Innovation Solution
The method involves forming data into packets of uniform size, applying an algorithm for modification, and using the algorithm as a lookup table for secure searching, including techniques like index shuffling, padding, and perturbation, allowing for encrypted search and retrieval without decrypting the entire dataset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional encryption methods are used to secure data, then data security is improved, but programmatic search capability deteriorates because the entire corpus must be decrypted for searching
Solution Approach 1:
The patent segments the encrypted data into multiple partitions and applies different encryption keys to each partition. This allows selective decryption of only the relevant partitions needed for search operations, rather than decrypting the entire corpus, thus maintaining security while improving search efficiency.
Solution Approach 2:
The patent performs preliminary encryption of data partitions with multiple keys before storage. During search operations, the system can quickly determine which partitions contain relevant data and decrypt only those partitions in advance, reducing the time and resources needed for actual search execution.
2Ease of operation
If data is stored in unencrypted form to enable search functions, then search capability is improved, but data security deteriorates due to vulnerability to unauthorized access
Solution Approach 1:
The patent divides encrypted data into multiple partitions, each encrypted with a different key. This segmentation allows the system to maintain full encryption for security while enabling search capability by allowing selective decryption of specific partitions based on search queries, rather than requiring all data to be unencrypted.
Solution Approach 2:
The patent changes the encryption parameter by using multiple different encryption keys for different data partitions. This allows the system to adjust the level of encryption applied to each partition based on access patterns and search requirements, balancing security and search capability dynamically.
3Measurement precision
If the entire encrypted corpus is decrypted for programmatic search, then complete search accuracy is improved, but time consumption and resource usage worsen
Solution Approach 1:
The patent segments the data corpus into multiple partitions that can be independently processed. During search operations, only the partitions relevant to the search query are decrypted and searched, maintaining search accuracy for the relevant data while avoiding the time cost of decrypting irrelevant partitions.
Solution Approach 2:
The patent applies partial decryption action by decrypting only the specific data partitions needed for the current search query, rather than decrypting the entire corpus. This partial action maintains search accuracy for the relevant data while significantly reducing the time and resources required compared to full corpus decryption.
Data Source
AI summary
Systems and methods are disclosed for securely storing and programmatic searching of data files. The invention includes storing datafiles in fixed-sized packets of data that are subjected to fixed shuffle of the data elements (with or without prior fixed padding and with or without prior fixed perturbation), and target search elements are identified by way of the fixed shuffled indices, which are encrypted by conventional methods and decrypted for search by credentialed users.