Data Partitioning Strategy for Secure Cloud Query Processing

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Solution Overview

Problem

Distributed databases face security challenges when storing sensitive data in public clouds, as encryption and decryption processes expose data to risk, and existing solutions like partial homomorphic encryption and hybrid clouds do not fully leverage scalability and reliability.

Innovation Solution

A data partitioning strategy that dynamically determines which columns to store in a private cloud in plaintext and which in a public cloud, using appropriate encryption schemes, based on sensitivity and query workloads, with the ability to update the partitioning strategy based on query weights and system constraints.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If sensitive data is stored in public cloud, then storage scalability and reliability are improved, but data security deteriorates due to encryption/decryption exposure risks

Engineering Contradiction:

Improvedata storage reliabilityVSAvoiddata security risk

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent segments data into sensitive and non-sensitive columns, storing sensitive columns in encrypted format in the public cloud while keeping non-sensitive columns in plaintext. This segmentation allows the system to leverage public cloud reliability for storage while minimizing security exposure by encrypting only the necessary sensitive portions.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies different quality characteristics to different parts of the data: sensitive columns receive encryption protection when stored in the public cloud, while non-sensitive columns remain in plaintext for efficient access. This local quality approach ensures security measures are applied precisely where needed without compromising overall system performance.

Inventive Principle:

Principle #3Local quality

2Productivity

If all columns are stored in plaintext in public cloud, then query processing efficiency is improved, but data security deteriorates

Engineering Contradiction:

Improvequery processing efficiencyVSAvoiddata security risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent divides database columns into two categories: sensitive columns that require encryption and non-sensitive columns that can be stored in plaintext. This segmentation enables the system to maintain high query processing efficiency for non-sensitive data while providing security protection for sensitive data through encryption.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the storage format parameter for different columns based on their sensitivity classification. Sensitive columns are stored in encrypted format to ensure security, while non-sensitive columns are stored in plaintext format to optimize query processing efficiency. This parameter change approach allows the system to balance security and performance requirements.

Inventive Principle:

Principle #35Parameter changes

3Object-affected harmful factors

If sensitive columns are encrypted in public cloud, then data security is improved, but query processing complexity increases

Engineering Contradiction:

Improvedata securityVSAvoidquery processing complexity

Core Design Contradiction:

Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The patent segments the database schema into sensitive and non-sensitive columns, allowing the query processing system to handle encrypted and plaintext data differently. This segmentation reduces query processing complexity by enabling straightforward access to non-sensitive plaintext columns while applying encryption-only protection to sensitive columns, avoiding the need for complex decryption operations in all queries.

Inventive Principle:

Principle #1Segmentation

4Reliability

If data is partitioned between private and public cloud, then security and scalability are both improved, but system complexity increases

Engineering Contradiction:

Improvesystem reliabilityVSAvoiddistributed system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the database storage across two cloud environments: private cloud for sensitive columns requiring high security and public cloud for non-sensitive columns requiring scalability. This segmentation allows the system to leverage the security advantages of private cloud and the scalability advantages of public cloud while managing complexity through clear separation of concerns and automated partitioning strategies.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11194838B2Generating a data partitioning strategy for secure and efficient query processing

Publication Date: 2021.12.07 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

Methods, systems, and computer program products for generating a data partitioning strategy for secure and efficient query processing are provided herein. A computer-implemented method includes obtaining at least (i) a database schema associated with a database and (ii) a query workload associated with the database; and generating, based at least in part on the database schema and the query workload, a distributed database structure for the database that (i) stores a first set of columns of the database within a private cloud environment in a plaintext format and (ii) stores a second set of columns of the database in a public cloud environment, wherein the second set of columns is stored in either a plaintext format or an encrypted format based on whether the second set of columns comprises sensitive data.