Encrypted Multi-Maps for Hiding Individual Query Volumes
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Solution Overview
Problem
Existing end-to-end encryption technologies face challenges in hiding the volume of individual queries, allowing adversaries to infer underlying data and queries through data leakage, even when the data is encrypted.
Innovation Solution
The system transforms input multi-maps into two encrypted multi-maps, one with consistent tuple lengths and another for remaining values, using techniques like logarithmic choices, cuckoo hashing, and garbled bloom filters to obscure query volumes while revealing some cumulative statistics, thereby preventing adversaries from learning individual query volumes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is fully encrypted using end-to-end encryption, then data security is improved, but query volume information becomes leakable to adversaries
Solution Approach 1:
The patent segments the encrypted data structure into multiple encrypted data structures (e.g., multiple encrypted B-trees or hash tables). Each segment is independently encrypted and stored, such that no single segment reveals the total query volume. When a query is executed, the system distributes the query across multiple segments, and the adversary observing any single segment cannot determine the actual query volume from the encrypted data structure.
2Reliability
If encrypted data structures are used to hide data content, then confidentiality is improved, but the shape and distribution of the data structure become leakable
Solution Approach 1:
The patent applies different encryption schemes or transformation techniques to different parts of the data structure. For example, certain regions or levels of the encrypted data structure are transformed to have uniform appearance characteristics, while maintaining the ability to perform efficient queries. This local transformation ensures that even if the overall shape is visible, local variations that could reveal sensitive information about data distribution are suppressed.
3Reliability
If traditional encryption schemes are applied to multi-maps, then data protection is improved, but storage and query efficiency deteriorate
Solution Approach 1:
The patent transforms the encrypted multi-map into a new data structure format that changes key parameters: it reorganizes the data into a hierarchical or segmented structure where encryption is applied at multiple levels. This transformation maintains polynomial-time query complexity by ensuring that query operations can proceed without decrypting the entire data structure, thus preserving efficiency while enhancing protection.
Data Source
AI summary
A volume hiding structured encryption system and method is provided. According to some embodiments, the system leverages the principle that a STE scheme can leak cumulative information about the query volumes of the data stored in multi-map format, while still hiding the volumes of client queries at query time. According to various examples, the system implements encryption schemes that have smaller storage and better query complexity than the current state-of-the-art, for some input distributions. According to one example, the STE schemes are adapted to the input data structure in order to improve efficiency over known approaches. Further examples includes schemes that are configured to partition a multi-map into smaller multi-maps, and use different allocation functions for different efficiency trade-offs: (i) random allocation, (ii) cuckoo-hashing allocation, and (iii) Garbled Bloom Filter allocation. In one example, the GBF construct enables a stash-less encryption scheme that hides query volumes.