SOAR Mitigation Validation for Coordinated Cyber Threat Response
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Solution Overview
Problem
Existing cybersecurity systems struggle to effectively manage and validate the mitigation of sophisticated cyber threats due to the complexity and diversity of cybersecurity applications, requiring constant updates and often failing to work in concert, leading to inefficient and inadequate protection.
Innovation Solution
A computer-implemented method and system utilizing a security orchestration, automation, and response (SOAR) system to manage and validate cybersecurity mitigation by accessing multiple threat protection applications, analyzing inputs, initiating responses, and validating mitigation success using a library of metrics and machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple cybersecurity threat protection applications are deployed to handle sophisticated cyber threats, then the coverage and detection capability are improved, but the system complexity and difficulty of coordination increase
Solution Approach 1:
The patent combines multiple cybersecurity threat protection applications into a unified system that shares common data structures, metrics libraries, and validation mechanisms. This merging reduces coordination complexity while maintaining comprehensive threat coverage through standardized interfaces and centralized management of security operations.
Solution Approach 2:
The system implements universal data structures and common metrics that can be applied across different cybersecurity applications and threat types. This multi-functionality allows the same framework to handle various cyber threats (malware, phishing, DDoS, etc.) without requiring separate coordination mechanisms for each application.
2Reliability
If cybersecurity systems are updated frequently to counter evolving threats, then the protection effectiveness is improved, but the loss of time and operational disruption increase
Solution Approach 1:
The system performs preliminary validation of mitigation effectiveness using pre-defined success metrics and validation rules. By establishing validation criteria in advance and continuously monitoring against these metrics, the system can quickly verify whether updates are working without requiring lengthy testing or deployment cycles, thus reducing update time while maintaining detection accuracy.
Solution Approach 2:
The system implements continuous feedback loops that monitor cybersecurity metrics and automatically adjust mitigation strategies. This real-time feedback mechanism allows the system to respond to evolving threats immediately without requiring frequent manual updates, as the system self-optimizes based on observed threat patterns and validation results.
3Measurement precision
If manual validation of cybersecurity mitigation is performed to ensure effectiveness, then the measurement precision is improved, but the productivity and response time decrease
Solution Approach 1:
The system performs automated self-validation of mitigation effectiveness by continuously monitoring predefined success metrics and comparing actual performance against expected outcomes. This self-service validation mechanism maintains high measurement precision through systematic metric tracking while eliminating manual validation steps, thus preserving productivity and enabling rapid threat response.
Solution Approach 2:
The system uses quantifiable success metrics and measurable parameters to validate mitigation effectiveness objectively. By transforming qualitative validation judgments into quantitative metric comparisons (e.g., threat detection rate, response time, containment effectiveness), the system achieves both high measurement precision and automated efficiency, eliminating the need for slow manual assessment.
Data Source
AI summary
Disclosed embodiments provide techniques for cybersecurity operations mitigation management. A plurality of network-connected cybersecurity threat protection applications is accessed. A plurality of inputs from the cybersecurity threat protection applications is received in response to one or more cybersecurity events. A cybersecurity mitigation is initiated, triggered by an analysis of the one or more security events. The mitigation is performed by at least one of the threat protection applications. The analysis is performed on a network-connected computer platform. The network-connected computer platform comprises a security automation and response system (SOAR) that enables the analysis, managing, and validating of the cybersecurity event mitigation. The mitigating and validating are based on a library of cybersecurity mitigation success metrics, including validators, success criteria, and time factors. The cybersecurity mitigation success metric library is maintained and updated based on a machine learning model.