Distributed Network Cyber Resilience Verification with Adaptive Monitoring
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Solution Overview
Problem
Existing cybersecurity systems face challenges in maintaining real-time adaptability and scalability to dynamic threats within distributed entity or third-party networks (DETPNs), often relying on static assessments that fail to capture evolving risks and vulnerabilities, leading to delayed detection and response to cybersecurity incidents.
Innovation Solution
Implement automated monitoring and real-time compliance evaluation using compliance parameters and tokens to assess and track cybersecurity states across DETPNs, integrating knowledge graphs for contextual inferences and adaptive timing mechanisms to ensure continuous validation and verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated monitoring and real-time compliance evaluation are implemented, then the ability to detect and respond to cybersecurity incidents is improved, but the system complexity and resource requirements increase
Solution Approach 1:
The system segments the cybersecurity monitoring function into distributed compliance evaluation modules across multiple entities in the DETPN. Each entity independently evaluates its own compliance state using local compliance parameters, eliminating the need for a centralized complex monitoring system while improving detection reliability through distributed validation.
Solution Approach 2:
Entities within the DETPN perform self-evaluation of their compliance levels using automated monitoring of their own cybersecurity states. This self-service approach reduces system complexity by eliminating external monitoring overhead while maintaining reliable incident detection through autonomous compliance assessment.
2Speed
If continuous real-time compliance evaluation is performed, then the responsiveness to emerging threats is improved, but the computational resources and energy consumption increase
Solution Approach 1:
The system performs compliance evaluation at discrete timing phases rather than continuous monitoring. Compliance levels are determined at specific intervals based on changes in cybersecurity state or environmental data, reducing computational resource consumption while maintaining rapid response capability when threats emerge.
Solution Approach 2:
The compliance evaluation frequency is dynamically adjusted based on the detected cybersecurity state. During periods of stability, evaluations occur less frequently to conserve resources. When changes or threats are detected, the system increases evaluation frequency to improve response speed, optimizing the balance between responsiveness and resource consumption.
3Measurement precision
If comprehensive compliance parameters are established for all entities, then the measurement accuracy of cybersecurity resilience is improved, but the difficulty of implementation and maintenance increases
Solution Approach 1:
The system establishes compliance parameters tailored to local conditions of each entity within the DETPN rather than applying uniform comprehensive parameters. Each entity receives compliance parameters specific to its cybersecurity context, maintaining measurement precision for resilient assessment while reducing implementation difficulty through customization.
Solution Approach 2:
The compliance parameter framework is designed to be universally applicable across different entities while accommodating local variations. A core set of universal compliance parameters applies to all entities, with optional additional parameters for specific contexts, reducing overall implementation complexity while maintaining comprehensive measurement precision.
4Productivity
If manual compliance assessment methods are used, then the system simplicity is maintained, but the productivity and efficiency of cybersecurity verification decrease
Solution Approach 1:
The system performs preliminary automated evaluation of compliance parameters and generates compliance level determinations before formal verification is needed. This preliminary automation reduces the workload for manual verification processes, improving overall productivity while maintaining system simplicity through phased automation.
Solution Approach 2:
The system implements automated feedback loops where compliance evaluation results are automatically communicated to entities and used to adjust future monitoring. This automation feedback mechanism increases verification efficiency by eliminating repetitive manual assessment while keeping the overall system architecture simple through standardized feedback protocols.
Data Source
AI summary
Systems, methods, and computer-readable storage media for compliance verification and validation of cyber resilience in a distributed entity or third-party network (DETPN). Some methods can include generating or identifying, by one or more processing circuits, one or more compliance parameters for a plurality of entities or third-parties on the DETPN. Some methods can include determining, by the one or more processing circuits, at least one compliance level. Some methods can include receiving or identifying, by the one or more processing circuits, environmental data of the DETPN. Some methods can include determining, by the one or more processing circuits at a second timing phase, an updated at least one compliance level for at least one of the plurality of entities or third-parties based at least on the environmental data. In some implementations, some methods can include generating and storing, by the one or more processing circuits, one or more tokens.