Message Routing Graph for Privacy Control in Event Processing
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Solution Overview
Problem
In networked computer systems, especially in complex event processing systems like Smart Cities, it is challenging to control and manage data privacy effectively, particularly when data is gathered from various external sources, making it difficult for individuals to determine how their private data is used and to prevent misuse by unintended entities.
Innovation Solution
A computer system with inbound and complex event processing modules that analyze data and manage communication relationships based on predefined conditions, allowing data owners to specify data usage constraints, enabling granular control over data sharing and privacy, and dynamically adjusting communication relations to ensure compliance with pre-defined pre-conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is gathered from large quantities of external entities in complex event processing systems, then the system can provide useful aggregate data for optimization purposes, but it becomes very hard to implement control mechanisms where individuals can determine how their private data is utilized and prevent misuse by unintended entities
Solution Approach 1:
The patent segments data control into multiple hierarchical levels: individual data granularity control (frequency, precision, resolution), correlation control with other data sources, and conditional use specifications. This segmentation allows the system to manage complex data control requirements by breaking them down into manageable, configurable parameters that individuals can specify without overwhelming complexity.
Solution Approach 2:
The patent introduces an intermediary control layer between data collection and data processing that enforces user-specified constraints. This intermediary mechanism translates individual privacy preferences into actionable control rules that the system automatically applies, mediating between the need for aggregate data utilization and individual data protection without requiring direct individual involvement in each data use decision.
2Reliability
If individual users protect privacy of their data, then data security and privacy are maintained, but the system loses access to valuable individual data that could optimize technical processes
Solution Approach 1:
The patent implements dynamic data sharing where individuals can specify different levels of data granularity (frequency, precision, resolution) and conditional usage scenarios. This dynamic approach allows data protection to be adjusted based on specific contexts and purposes, enabling process optimization when appropriate while maintaining privacy protection when needed, rather than using static all-or-nothing privacy controls.
Solution Approach 2:
The patent changes the parameters of data sharing by allowing individuals to control data granularity (frequency, precision, resolution), correlation with other sources, and conditional usage. These parameter changes enable the system to transform private individual data into usable aggregate data for process optimization while maintaining individual privacy control, effectively converting the data from a privacy risk into an optimization resource.
3Adaptability or versatility
If the system allows flexible data usage by third parties under specific conditions, then valuable data can be utilized for aggregate purposes, but implementing and enforcing these control mechanisms becomes increasingly difficult at scale
Solution Approach 1:
The patent creates a universal control framework that handles multiple data control requirements through a unified mechanism. The same infrastructure manages individual data granularity control, correlation control, conditional usage specifications, and enforcement across the entire system. This universal approach enables flexible data usage scenarios while maintaining system scalability, as the multi-functional control mechanism serves all data types and usage scenarios without requiring separate implementation for each case.
Data Source
AI summary
Message routing techniques include use of at least one controller module configured to maintain a graph. The graph defines communication relations between a plurality of message communication modules. Each communication relation defines a particular message type for a particular pair of modules. The plurality of message communication modules includes a first module configured to receive a message wherein the received message has a message type and is associated with least one pre-condition. Upon verification of an acceptance condition of the at least one pre-condition the received message is accepted if the acceptance condition is fulfilled. Upon verification of a generating condition of the at least one pre-condition, the first module generates a generated message directed to at least a second module or an external data consumer in accordance with the graph if the generating condition is fulfilled.