SOAR Platform Automating Cybersecurity Workflows via AI Policy Translation
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Solution Overview
Problem
The increasing complexity of cybersecurity threats and regulatory compliance requirements makes it challenging for organizations to maintain consistent and effective cybersecurity policies across their networks and systems, especially as they grow and expand globally, with existing management systems often requiring significant staff resources and struggling to integrate multiple security applications.
Innovation Solution
The implementation of an AI-driven cybersecurity management system using a SOAR platform that assimilates compliance requirements, translates them into policies, and generates workflows for managing cybersecurity threats, leveraging natural language processing and machine learning to automate the process and ensure conformity with regulatory standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations use multiple layers of network security applications to respond to cybersecurity threats, then security coverage is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple cybersecurity applications and functions into a unified SOAR platform that integrates threat detection, response, compliance monitoring, and workflow automation. This consolidation maintains comprehensive security coverage while reducing the complexity of managing separate security layers through a single integrated system.
Solution Approach 2:
The SOAR platform is designed as a universal system that performs multiple functions including threat detection, incident response, compliance verification, and automated workflow execution. This multi-functionality eliminates the need for separate specialized tools for each security function, thereby reducing overall system complexity while maintaining comprehensive protection.
2Manufacturing precision
If organizations manually manage and update cybersecurity policies to ensure compliance, then policy accuracy is improved, but time consumption increases
Solution Approach 1:
The system pre-configures compliance workflows and policies based on regulatory requirements before incidents occur. The SOAR platform automatically updates policies in advance of compliance changes, eliminating the need for manual policy revisions during critical periods and reducing overall time consumption while maintaining accuracy.
Solution Approach 2:
The system continuously monitors compliance status and automatically adjusts policies based on real-time feedback from regulatory updates and organizational changes. This closed-loop feedback mechanism ensures policy accuracy without requiring manual review, as the system self-corrects based on incoming information.
3Reliability
If organizations deploy comprehensive security applications across global networks, then security coverage is improved, but management difficulty increases
Solution Approach 1:
The patent segments global security management into region-specific workflows that can be independently configured and executed. Each regional compliance requirement is handled as a separate modular workflow within the SOAR platform, allowing localized security coverage while simplifying overall management through standardized templates and automated deployment.
Solution Approach 2:
The SOAR platform enables self-service security management by automatically deploying, monitoring, and adjusting security workflows across global networks without requiring manual intervention. The system self-manages compliance verification and security updates, dramatically reducing management difficulty while maintaining comprehensive coverage.
4Productivity
If organizations use AI and ML to automate cybersecurity workflows, then productivity is improved, but implementation complexity increases
Solution Approach 1:
The patent introduces an intermediary layer of pre-trained ML models and AI frameworks that simplify the implementation of automation. These pre-built components act as mediators between raw data and automated decisions, reducing implementation complexity by providing ready-to-deploy intelligence rather than requiring custom model development.
Solution Approach 2:
The system implements automation by changing operational parameters rather than fundamentally altering workflows. ML models analyze existing security data and automatically adjust workflow parameters such as alert thresholds, response timing, and compliance verification frequency, achieving high productivity with minimal implementation complexity.
Data Source
AI summary
Disclosed embodiments provide techniques for cybersecurity AI-driven workflow generation using policies. A set of cybersecurity threat protection applications is accessed and managed by a security orchestration, automation, and response (SOAR) platform. The cybersecurity threat protection applications are deployed across a managed cybersecurity network. One or more cybersecurity network compliance requirements are assimilated into the SOAR platform by translating the compliance requirements into one or more cybersecurity application policies and work processes. The assimilation is accomplished using an AI user interface with natural language processing. The cybersecurity application policies provide conformity with the compliance requirements. The application policies generate one or more cybersecurity application workflows for the managed cybersecurity network. The SOAR platform executes the cybersecurity workflow. The workflow is enabled by an embedded universal data layer that maps the cybersecurity threat protection application inputs and outputs to the SOAR platform.