Data Analytics Key Sharing for Privacy-Preserving Policy Control

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Solution Overview

Problem

Existing data analytics systems face challenges in ensuring privacy and enforcing data usage policies without relying on centralized trust, leading to potential data breaches and metadata leakage, especially in settings like Apache Kafka where trusted hardware is not deployed, and existing ORAM constructions are computationally expensive.

Innovation Solution

A data analytics system using complementary keys generated through a secret sharing based cryptographic algorithm, combined with symmetric homomorphic stream encryption, to encrypt and store data across two non-colluding servers, ensuring policy-controlled data usage and metadata protection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data is shared by data owners for analytics, then data utility and analytics capability are improved, but data leakage risk and unauthorized sharing increase

Engineering Contradiction:

Improvedata analytics capabilityVSAvoiddata leakage risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent segments data into multiple independent shares that must be combined to reconstruct the original data. Each share alone reveals no information about the underlying data, enabling analytics while preventing unauthorized reconstruction and leakage.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces secret sharing schemes and cryptographic protocols as intermediaries between data owners and analytics systems. These intermediaries enable secure computation on encrypted data without exposing the actual data values to the analytics processor.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If centralized trusted authorities are used for policy enforcement, then data usage control is improved, but trust vulnerability and breach risk increase

Engineering Contradiction:

Improvedata usage controlVSAvoidtrust authority vulnerability

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent segments the trust function by distributing secret shares to multiple semi-trusted parties instead of relying on a single centralized authority. This segmentation ensures that no single party can compromise the entire system, as they would need to collude with a threshold number of parties to reconstruct secrets.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent assigns different roles and permission levels to different parties in the distributed system. Each party has specific local capabilities and constraints, with data owners maintaining control over their own data shares and analytics systems having limited access to perform computations without seeing actual data.

Inventive Principle:

Principle #3Local quality

3Loss of information

If data policies are encrypted to hide metadata, then metadata privacy is improved, but computation complexity and overhead increase

Engineering Contradiction:

Improvemetadata leakageVSAvoidcomputation overhead

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent performs preliminary encryption of data and policies before they are submitted to the analytics system. By encrypting data in advance using secret sharing schemes, the system eliminates the need for complex real-time encryption during analytics operations, reducing overall computational overhead.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces complex cryptographic protocol execution with pre-computed encrypted structures. Instead of performing heavy cryptographic operations during each analytics query, the system uses pre-established encrypted data shares that can be processed more efficiently.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of information

If ORAM constructions are used to support multi-owner settings, then oblivious data access is improved, but computation cost increases heavily

Engineering Contradiction:

Improveoblivious access capabilityVSAvoidcomputation efficiency

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The patent segments the oblivious access problem by applying secret sharing to divide data access patterns into multiple independent shares. This allows the system to achieve oblivious access properties without requiring the heavy computational overhead of full ORAM constructions, as each share can be accessed independently without revealing access patterns.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12625976B2Data analytics system and its operation

Publication Date: 2026.05.12 CITY UNIVERSITY OF HONG KONG

AI summary

A method for operating a data analytics system includes storing, at a first server system of the data analytics system, a first key associated with a data provider and/or storing, at a second server system of the data analytics system, a second key associated with the data provider. The first key and the second key are complementary keys generated using a secret sharing based cryptographic algorithm based on a policy arranged to control usage of data provided by the data provider. The first key and the second key are arranged to facilitate performing of a data analytics operation at the data analytics system.