Risk Management Platform for Data Security via Virtual Modeling
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Solution Overview
Problem
There is a growing need for improved systems and methods to manage and reduce risks associated with the exposure of personal and sensitive data handled by computing systems, as entities seek to mitigate risks related to data-related incidents such as theft and misuse.
Innovation Solution
A method and system that identify potential risk triggers by assessing risk remediation data from similarly situated entities, scanning data models to determine the impact on specific data assets, and taking actions such as modifying encryption levels or access permissions to remediate the effects of these risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entities implement comprehensive risk management systems to identify and mitigate data security risks, then data security and compliance improve, but system complexity and implementation cost increase
Solution Approach 1:
The system creates a virtual copy of the entity's data assets, processing activities, and risk triggers in a simulated environment. This virtual replica allows the system to assess risk scenarios and test remediation actions without affecting the actual data infrastructure, thereby improving security assessment accuracy while avoiding the complexity of implementing comprehensive physical security measures across all systems.
Solution Approach 2:
The system introduces a risk management platform as an intermediary layer between data assets and security controls. This intermediary assesses risk triggers, determines relevance to data assets, and identifies appropriate remediation actions, simplifying the overall system architecture by centralizing risk management functions rather than embedding security measures throughout every data processing component.
2Reliability
If entities conduct thorough risk assessments and remediation actions to protect data, then data protection improves, but time required for assessment and response increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing virtual copies of data assets and processing activities, and pre-defining risk trigger criteria. When actual risk triggers occur, the system can immediately compare them against pre-established criteria and virtual models, significantly reducing assessment time while maintaining thoroughness in protecting data assets.
Solution Approach 2:
By maintaining virtual copies of data assets and processing activities, the system enables rapid assessment of risk scenarios without requiring time-consuming analysis of actual system configurations. The virtual models allow for quick determination of risk relevance and automated identification of remediation actions, reducing response time while ensuring comprehensive data protection.
3Speed
If entities monitor and respond to risk triggers in real-time to prevent data breaches, then security responsiveness improves, but computational resources and processing overhead increase
Solution Approach 1:
The system uses virtual copies of data assets and processing activities to simulate and assess risk scenarios. This allows the system to perform comprehensive risk analysis and determine remediation actions using computational resources in a controlled virtual environment, improving response speed for actual security incidents while managing computational overhead by avoiding the need to continuously process all possible risk scenarios in the actual system.
Solution Approach 2:
The system extracts risk assessment and remediation determination functions from the main data processing operations and places them in a separate risk management platform. This extraction allows real-time monitoring and response to risk triggers without continuously consuming computational resources for comprehensive risk analysis, as only relevant risk scenarios are processed when triggers occur.
Data Source
AI summary
In various embodiments, a system may be configured to substantially automatically determine whether to take one or more actions in response to one or more identified risk triggers (e.g., data breaches, regulation change, etc.). The system may, for example: (1) compare the potential risk trigger to one or more previous risks triggers experienced by the particular entity at a previous time; (2) identify a similar previous risk trigger (e.g., one or more previous risk triggers related to a similar change in regulation, breach of data, type of issue identified, etc.); (3) determine the relevance of the current risk trigger based at least in part on a determined relevance of the previous risk trigger; and (4) determine whether to take one or more actions to the current risk trigger based at least in part on one or more determined actions to take in response to the previous, similar risk trigger.