AI Security Posture Generation From Natural Language Intent
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Creating and updating a security posture for an organization is a long, tedious, and resource-intensive task that often requires specialized knowledge and technical expertise, leading to inadequate implementations that may not provide the intended protection.
Innovation Solution
Utilizing an artificial intelligence (AI) model to convert natural language descriptions of security intent into computer-executable security posture features, leveraging generative AI techniques to generate and update security postures efficiently and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional manual methods are used to create and update security posture, then specialized knowledge and technical expertise are required, but the process becomes long, tedious, and resource-intensive
Solution Approach 1:
The patent replaces manual mechanical processes of security posture creation with an AI model that automatically generates security posture configurations. The AI model processes natural language security requirements and transforms them into executable security configurations, eliminating the need for manual technical expertise and significantly reducing the time required while maintaining or improving security quality.
Solution Approach 2:
The system enables security posture generation to be self-service through the AI model, which autonomously interprets security requirements and generates appropriate configurations without requiring specialized human intervention. The AI model serves itself by having built-in knowledge of security best practices and organizational policies, allowing it to independently produce high-quality security postures.
2Reliability
If manual security posture creation is performed, then technical expertise is required, but implementations become inadequate and may not provide intended protection
Solution Approach 1:
The AI model acts as an intermediary between natural language security requirements and executable security configurations. It translates high-level security intents into detailed, accurate security implementations, ensuring that the intended protection is properly realized without requiring end users to possess complex technical expertise.
Solution Approach 2:
The system changes the parameter of security posture creation from manual configuration to AI-generated configuration. This parameter change transforms the process from one requiring specialized human knowledge to an automated process that leverages the AI model's trained understanding of security principles, thereby improving implementation quality while reducing complexity requirements for users.
3Adaptability or versatility
If traditional methods are used to update security posture, then resource-intensive processes are required, but keeping up with evolving cybersecurity specifications becomes difficult
Solution Approach 1:
The system incorporates feedback mechanisms where the AI model continuously learns from evolving security specifications and organizational policies. The model receives feedback about security requirements changes and adjusts its generation process accordingly, enabling automatic adaptation to new security standards without requiring manual reconfiguration or extensive resources.
Solution Approach 2:
The security posture generation process is made dynamic through the AI model, which can rapidly adapt to changing security requirements. The system transitions from static, manual update processes to a dynamic automated process that can respond quickly to evolving cybersecurity specifications, improving both adaptability and productivity.
Data Source
AI summary
A system and method for exploring security rule chains in a security platform. The method includes providing a natural language description of a set of features of a security posture of an organization as a first input to a trained artificial intelligence (AI) model, providing telemetry data pertaining to a computing environment of the organization as a second input to the trained AI model, obtaining one or more outputs from the trained AI model, and extracting, from the one or more outputs, a set of generated features for the security posture of the organization.