Cyber Resilience Identity Tokenization for Dynamic Threat Response
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cybersecurity systems lack integrated incident response capabilities, operate in isolation, and rely on static defenses, leading to delayed responses, fragmented visibility, and increased vulnerabilities due to evolving threats and infrastructure changes.
Innovation Solution
A customized cybersecurity framework that models cyber resilience data using cyber resilience identities and associated metadata, incorporating tokenization and decentralized ledgers to enhance dynamic monitoring and response, and integrates with vendors for targeted protection strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cybersecurity systems operate in isolation with static defenses, then system simplicity is maintained, but response capability and visibility are fragmented and delayed
Solution Approach 1:
The system segments cyber resilience data into distinct categories (firmographics, safeguards, performance, policy, incident, claims) and models them as separate entities with relationships. This allows complex data to be managed through modular components while enabling comprehensive incident response through their interconnectedness.
Solution Approach 2:
The patent merges multiple isolated cybersecurity systems into a unified framework that integrates incident response, vulnerability management, and compliance monitoring. The cyber resilience identity model combines diverse data types and system functions into a single coordinated approach, improving response capability while maintaining manageable complexity through structured integration.
2Adaptability or versatility
If static defenses are used, then implementation simplicity is maintained, but adaptability to evolving threats is reduced
Solution Approach 1:
The system transitions from static to dynamic defenses by continuously updating cyber resilience identities with new data from multiple sources. The framework dynamically adapts to evolving threats through real-time monitoring, automated updates, and flexible policy enforcement that responds to changing security landscapes without requiring complete system redesign.
Solution Approach 2:
The framework changes parameters such as risk thresholds, compliance requirements, and monitoring priorities based on evolving threat intelligence and organizational needs. This allows the system to adapt its protective measures dynamically while maintaining a manageable framework structure through parameterization rather than architectural complexity.
3Loss of information
If comprehensive cyber resilience data is collected and managed, then visibility and response accuracy improve, but data management complexity increases
Solution Approach 1:
The system segments comprehensive cyber resilience data into organized entities (firmographics, safeguards, performance, policy, incident, claims) with defined relationships. This segmentation maintains high data visibility and accessibility while reducing management complexity through structured categorization and standardized access patterns.
Solution Approach 2:
The framework creates virtual copies of cyber resilience data through the cyber resilience identity model, allowing multiple systems to access and monitor the same data without physical duplication. This eliminates data redundancy and management complexity while maintaining comprehensive visibility through shared data references.
4Measurement precision
If real-time monitoring and dynamic updates are implemented, then security posture visibility improves, but processing requirements and system resources increase
Solution Approach 1:
The system implements partial real-time monitoring focused on critical security events and key performance indicators rather than continuous processing of all data. This approach maintains high security posture visibility for most important aspects while reducing processing resource consumption by selectively monitoring and updating only when necessary.
Solution Approach 2:
The framework enables systems to self-monitor and self-update their cyber resilience identities without requiring continuous external processing. Entities can autonomously report their own security posture, and the system automatically updates relevant data, reducing the need for intensive external processing resources while maintaining real-time visibility.
Data Source
AI summary
Systems, methods, and computer-readable media for modeling cyber resilience data using cyber resilience identities and associated metadata are disclosed. A system can include one or more processing circuits configured to receive an access request for a cyber resilience identity from an entity or authorized entity. The access request can include a data structure compatible with a control structure for restricting updates or redemptions of a metadata object corresponding with the cyber resilience identity. The processing circuits can verify, using a control structure, the access data structure. The processing circuits can grant access to the metadata object and a performance event dataset to the entity or authorized entity. The processing circuits can decrypt the metadata object and provide access to the metadata object and the performance event dataset by facilitating retrieval using a secure interface.