Event Streaming Rules Engine for Secure Real-Time Notifications
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Solution Overview
Problem
Existing interaction event processing systems often delay and lack detailed notifications, especially outside regular business hours, due to disparate notification methods among different processing applications, leading to inefficiencies in data consumer information updates.
Innovation Solution
A computer-implemented method and system for real-time interactive event streaming that modifies interaction events to obscure personal information, using a rules engine to selectively notify data consumers with up-to-date event status changes across various processing applications, ensuring timely and relevant information delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple processing applications notify data consumers of event status changes in different manners, then each application can maintain its own notification methodology, but notification delays occur and important details are lost
Solution Approach 1:
The patent merges multiple disparate notification methods from different processing applications into a single standardized notification pipeline. The event store receives events from various sources and transforms them into a unified format that can be consumed by data consumers through consistent channels, eliminating the fragmentation that caused delays and information loss.
Solution Approach 2:
The event store acts as an intermediary component between processing applications and data consumers. It receives events from multiple applications, standardizes their format, and distributes them through a unified notification mechanism, thereby resolving the conflict between maintaining application-specific notification methods and achieving timely, consistent delivery.
2Loss of information
If all interaction events are transmitted to data consumers in real-time, then up-to-the-minute information is provided, but data consumers are overwhelmed with unnecessary information
Solution Approach 1:
The patent extracts and filters only the most relevant interaction events from the complete event stream using configurable rules. The event store applies filtering logic to identify high-priority events (such as payment failures, fraud detections, or critical status changes) and extracts these for notification, while excluding routine or low-priority events that would otherwise clutter the data consumer's information stream.
Solution Approach 2:
Instead of transmitting the complete event stream, the system applies partial action by selectively notifying data consumers about only the most critical events. This partial notification approach reduces the information processing load on data consumers while still providing timely alerts for important interactions, balancing information freshness with manageable complexity.
3Loss of information
If personal information of data publishers is included in event notifications, then complete event details are provided, but privacy security is compromised
Solution Approach 1:
The event store extracts and removes personal identifiable information (PII) from interaction events before transmitting them to data consumers. Sensitive fields such as names, addresses, and personal identifiers are stripped out or anonymized, while retaining the essential event context and status information needed for business operations, thus protecting privacy while maintaining event detail completeness.
Solution Approach 2:
The system creates anonymized copies of interaction events for notification purposes. Instead of transmitting the original events containing personal information, the event store generates sanitized copies with personal identifiers replaced by pseudonyms or removed entirely, allowing data consumers to process event details without exposure to sensitive personal data.
4Reliability
If a centralized event store processes all interaction events, then notification consistency is improved, but system complexity increases
Solution Approach 1:
The event store is designed as a universal component that handles multiple functions: receiving events from diverse processing applications, standardizing event formats, filtering relevant events, anonymizing personal information, and distributing notifications through multiple channels. This multi-functional design consolidates what would otherwise require multiple separate systems, achieving notification consistency without proportionally increasing overall system complexity.
Data Source
AI summary
Interactive event streaming can be provided in real-time and selectively transmitted to data consumers based on a rules engine. For example, a computer-implemented method described herein can include receiving a plurality of interaction events from at least one processing application. The method can include modifying the plurality of interaction events to produce a plurality of secured interaction events, wherein personal information of at least one data publisher in each secured interaction event of the plurality of secured interaction events is obscured. The method can further include selecting, based at least in part on a rules engine, at least one particular interaction event from the plurality of secured interaction events. Additionally, the method can include notifying a data consumer of the at least one particular interaction event from the plurality of secured interaction events.