Homomorphic POS Caching for Congested Payment Server Delays

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Solution Overview

Problem

Conventional payment processing systems experience delays and failures due to server congestion at recipient banks, leading to incomplete transactions and increased risk of hacking, with customers unaware of the need to retry or reverse transactions.

Innovation Solution

Implementing homomorphic encryption-based data caching at the Point of Sale (POS) with predictive latency estimation using LSTM neural networks, dynamic cache configuration, and intelligent queuing mechanisms to ensure payment success, even in the face of server issues.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If transaction data is cached locally at POS without encryption, then payment processing speed is improved, but security against hacking and tampering deteriorates

Engineering Contradiction:

Improvepayment processing speedVSAvoidsecurity risk

Core Design Contradiction:

SpeedVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary encryption of transaction data using homomorphic encryption before caching it locally at the POS device. This allows the data to be stored and processed in advance without compromising security, as the encryption is applied before the data leaves the secure environment.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Homomorphic encryption acts as an intermediary that enables local caching and processing of encrypted data without requiring decryption. The encrypted data serves as a mediator between the need for fast local processing and the requirement for secure data protection during storage and transmission.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Speed

If transactions are immediately processed without queuing, then real-time payment execution is improved, but reliability under server congestion deteriorates

Engineering Contradiction:

Improvereal-time payment executionVSAvoidtransaction success rate

Core Design Contradiction:

SpeedVSReliability

Solution Approach 1:

The system implements dynamic transaction queuing where the queue depth and retry behavior adapt based on real-time server status. When servers are congested, transactions are held in queue longer; when servers are available, transactions are processed immediately, optimizing both speed and reliability.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system continuously monitors server response times and transaction success rates, using this feedback to dynamically adjust queuing behavior. If server congestion is detected, the system increases queue depth and retry attempts; if servers are performing well, it reduces queuing to enable faster processing.

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If payment data is stored in local cache, then payment processing availability is improved, but device complexity increases

Engineering Contradiction:

Improvepayment processing availabilityVSAvoidPOS system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system extracts only the essential transaction data needed for caching and processing, separating it from the full payment payload. This reduces the complexity of local storage and management while maintaining the ability to process payments offline or during server unavailability.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of implementing a full-featured payment processing system locally, the POS device creates simplified copies of transaction data that can be cached and processed. These copies contain only the necessary information for basic operations, reducing device complexity while improving availability.

Inventive Principle:

Principle #26Copying

4Reliability

If homomorphic encryption is applied to all transaction data, then security is improved, but computational overhead increases

Engineering Contradiction:

Improvedata securityVSAvoidcomputational energy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system applies homomorphic encryption selectively to specific sensitive fields within transaction data rather than encrypting the entire payload. This maintains security for critical information while reducing the computational overhead associated with encrypting and processing all data.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system applies homomorphic encryption to only the portion of transaction data that requires protection, rather than encrypting everything. This partial application of encryption reduces computational energy consumption while still providing adequate security for the most sensitive information.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12574332B2Systems and methods for homomorphic encryption-based data caching

Publication Date: 2026.03.10 BANK OF AMERICA CORP

AI summary

The present disclosure details systems and methods for homomorphic encryption-based data caching. This technology detects transaction patterns via a monitoring module that liaises with both a payment system and an entity system. Prior to its processing, transaction data is encrypted with a homomorphic encryption module. A dynamic interface, aligned with a local point-of-sale (POS) cache, prioritizes data based on current transaction metrics. If a recipient server is busy, the transaction data is rerouted, stored in the POS's local cache, and queued. The transaction's success is gauged against a predefined cut-off time. Unsuccessful transactions within this window are slated for batch processing, yet resource processing proceeds while awaiting this batch processing.