Dynamic Cybersecurity Protection Valuation From Resilience Data
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Solution Overview
Problem
Existing cybersecurity systems face challenges such as lack of integrated incident response capabilities, complex procurement processes for third-party vendors, inability to dynamically adapt to changing threats, and insufficient visibility into organizational readiness and vulnerabilities.
Innovation Solution
A customized cybersecurity framework that integrates threat detection, response, and recovery, streamlines vendor engagement, and dynamically adapts to evolving threats by providing real-time data analysis and automated response protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time cybersecurity data is collected and analyzed from multiple data channels, then the accuracy of vulnerability identification and threat detection is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The system segments cybersecurity data collection into multiple specialized data channels (vulnerability data, threat intelligence, asset inventory, security controls) rather than using a single monolithic data collection mechanism. Each channel is handled by specific processing circuits that generate targeted metadata, dividing the complex task into manageable, specialized components that can be processed independently and then integrated.
Solution Approach 2:
The patent introduces metadata as an intermediary layer between raw cybersecurity data and protection parameter generation. Processing circuits generate structured metadata from various data channels, which then serves as the input for determining protection parameters. This intermediary metadata layer simplifies the complexity by providing a standardized, processed representation of diverse cybersecurity data sources.
2Adaptability or versatility
If protection parameters are dynamically updated based on real-time cybersecurity data, then the adaptability to changing threats is improved, but the computational resources and processing time required increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and preprocessing cybersecurity data through multiple data channels before threats materialize. Processing circuits generate metadata from vulnerability data, threat intelligence, and asset inventory in advance, so that when a threat occurs, the protection parameters can be quickly determined from pre-processed information rather than analyzing raw data from scratch during an incident.
Solution Approach 2:
The cybersecurity system performs self-service by automatically monitoring its own state through internal processing circuits that generate metadata about vulnerabilities, threats, and security controls. The system dynamically adjusts its own protection parameters based on this self-generated metadata without requiring external intervention, enabling continuous adaptation while managing computational resources efficiently through automated operations.
3Loss of information
If comprehensive cybersecurity metadata is generated from multiple data channels, then the visibility into organizational readiness is improved, but the data management and storage requirements increase
Solution Approach 1:
The system extracts only the essential and relevant information from comprehensive cybersecurity data channels to create focused metadata. Rather than storing and processing all raw data from vulnerability scans, threat intelligence feeds, and asset inventories, the processing circuits extract key parameters and characteristics that directly inform protection parameter determination, reducing data volume while maintaining visibility into organizational readiness.
Solution Approach 2:
The metadata generated by the processing circuits serves multiple functions simultaneously: it characterizes cyber incidents, determines protection parameters, assesses organizational readiness, and informs incident response decisions. This multi-functional metadata structure provides comprehensive visibility into readiness without requiring separate data structures for each purpose, optimizing data management efficiency.
4Speed
If automated response protocols are implemented based on metadata analysis, then the response speed to cyber incidents is improved, but the automation complexity and potential for false responses increase
Solution Approach 1:
The system implements feedback loops where processing circuits continuously generate metadata about the current cybersecurity state, which feeds into protection parameter determination and automated response protocols. The results of automated responses are fed back into the metadata generation process, allowing the system to learn from outcomes and adjust future responses. This feedback mechanism enables rapid automated response while managing complexity through iterative refinement based on actual performance data.
Data Source
AI summary
One system includes at least one processor configured to receive cybersecurity data using a network connection or interface established with one or more computing systems of at least one entity. The at least one processor can be configured to determine a state of cybersecurity of the at least one entity based on one or more safeguards or configurations implemented in the one or more computing systems in response to receiving the cybersecurity data, and the state of cybersecurity corresponds with a cybersecurity resilience to one or more security incidents. The at least one processor can be configured to generate or update a parameter corresponding with a cybersecurity evaluation, modeling tool, or third-party product based at least in part on the state of cybersecurity corresponding with the one or more safeguards or configurations.