Homomorphic Encryption for Secure Data Aggregation

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Solution Overview

Problem

Existing data aggregation protocols face challenges in protecting privacy, especially in minimal trust environments where parties do not trust each other, and are vulnerable to malicious access by aggregators seeking unauthorized decryption of encrypted data.

Innovation Solution

A method and system that utilize homomorphic encryption with public keys and seeds to ensure privacy preservation, allowing aggregation while preventing the aggregator from learning individual inputs, using pseudo-random generation and verification processes to secure data integrity even in malicious scenarios.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If a third-party aggregator is used to obtain and aggregate individual parties' inputs, then data aggregation can be performed, but the aggregator can learn all individual parties' data

Engineering Contradiction:

Improvedata aggregation capabilityVSAvoidprivacy of individual inputs

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system segments the aggregation process into two independent components: an aggregator that processes encrypted data without decryption capability, and a decryptor that holds decryption keys but cannot perform aggregation. This segmentation ensures that no single entity can both aggregate and decrypt, preventing the aggregator from learning individual inputs while maintaining aggregation functionality.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Homomorphic encryption serves as an intermediary mechanism that enables the aggregator to process data in encrypted form. The encryption scheme allows mathematical operations on ciphertexts to produce encrypted results that, when decrypted, match the operations performed on plaintexts. This intermediary layer protects individual inputs from the aggregator while enabling useful aggregation.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of information

If dataset anonymization is applied by removing unique identifiers, then linking data to owners becomes harder, but data can still be connected to owners and trust boundary problems remain

Engineering Contradiction:

Improvelinkability of data to ownersVSAvoidtrust boundary security

Core Design Contradiction:

Loss of informationVSReliability

Solution Approach 1:

The system extracts the decryption capability from the aggregator entity and places it in a separate decryptor entity. This extraction removes the security vulnerability where the aggregator could potentially link anonymized data to owners, as the aggregator never has access to decryption keys and thus cannot recover or associate individual inputs with their owners.

Inventive Principle:

Principle #2Taking out (Extraction)

3Reliability

If existing MPC protocols are used that assume semi-honest aggregators, then privacy can be protected under trust assumptions, but the solution cannot handle fully malicious parties that deviate from assigned methods

Engineering Contradiction:

Improveprivacy protection under trust assumptionsVSAvoidsecurity against malicious behavior

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system prepares cryptographic safeguards in advance by using homomorphic encryption schemes that are inherently resistant to malicious behavior. The encryption and verification mechanisms are built into the protocol beforehand, cushioning against potential malicious actions by the aggregator without requiring trust assumptions. This allows the system to handle fully malicious parties that deviate from assigned methods.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

4Loss of information

If homomorphic encryption is used to prevent aggregator from learning individual inputs, then privacy is preserved, but verification of operations on encrypted data becomes complex

Engineering Contradiction:

Improveprivacy of individual inputsVSAvoidverification mechanism complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system implements a feedback mechanism where the decryptor verifies aggregation results by decrypting them and checking against expected properties. This feedback loop ensures correctness of operations performed on encrypted data while maintaining privacy. The verification complexity is managed by having the decryptor, a trusted entity, perform the verification rather than requiring complex verification protocols among all parties.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11575501B2Preserving aggregation using homomorphic encryption and trusted execution environment, secure against malicious aggregator

Publication Date: 2023.02.07 SEAGATE TECH LLC

AI summary

A method includes providing a public encryption key and a seed to a party and receiving a first encrypted data set encrypted using the public encryption key and marked by the party with a first mark based on the seed. The method also includes aggregating the first encrypted data set into an aggregated data set at an aggregator and receiving an indication that a first operation associated with the party has been performed on the aggregated data set. In response to the receiving, updating the first encrypted data set of the aggregated data set by updating the first mark to a second mark according to the first operation, generating a verification encrypted data set according to at least the second mark and at least the corresponding first operation, verifying the aggregated data set by comparing the updated first encrypted data set and the verification encrypted data set.