Cyber Security Action Recommendation System Using ML Profiles
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Solution Overview
Problem
Current cyber security solutions are inefficient in detecting vulnerabilities and implementing effective security actions across digital environments, making it difficult to enhance network security and protect against cyber-attacks.
Innovation Solution
A processor-based apparatus and method that receives cyber and risk profiles to determine and implement recommended security actions, utilizing machine learning and fuzzy inferencing to identify vulnerabilities and generate user interface data structures for displaying implemented actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a wide array of variables is used in modern cyber security solutions, then the ability to account for multiple security factors is improved, but the time required to sort through and analyze these variables increases significantly
Solution Approach 1:
The patent replaces manual security analysis with an automated machine learning system that processes cyber profiles and risk factors. The ML model automatically generates security recommendations without requiring human analysts to manually sort through variables, thus maintaining comprehensive security coverage while dramatically reducing analysis time.
Solution Approach 2:
The system enables self-service security analysis by automatically processing cyber profiles, evaluating risk factors, and generating security recommendations without human intervention. The automated pipeline includes receiving cyber profiles, processing them through ML models, and outputting actionable security advice, allowing the system to serve itself in the security analysis process.
2Measurement precision
If comprehensive cyber security analysis is performed across multiple variables, then the detection of vulnerable areas is improved, but the difficulty of identifying specific actionable recommendations increases
Solution Approach 1:
The patent segments the complex security analysis into distinct processing stages: receiving cyber profiles, evaluating specific risk factors, generating security recommendations, and prioritizing actions. This segmentation transforms comprehensive vulnerability detection into manageable, actionable segments that are easier to interpret and implement.
Solution Approach 2:
The machine learning model acts as an intermediary between raw cyber profile data and actionable security recommendations. It processes the complex relationship between multiple risk factors and translates them into specific, prioritized security actions, making the connection between vulnerability detection and recommended actions clear and actionable.
3Ease of manufacture
If manual changes are made to cyber security solutions, then the ability to implement security actions is achieved, but the efficiency and difficulty of making suggested changes deteriorates
Solution Approach 1:
The patent replaces manual security implementation with automated machine learning-driven recommendations. The system automatically analyzes cyber profiles, identifies security gaps, and generates specific actionable recommendations, eliminating the need for manual security configuration and significantly improving implementation efficiency.
Solution Approach 2:
The system implements a feedback loop where security recommendations are generated based on analyzed cyber profiles and risk factors. This feedback mechanism provides continuous, data-driven guidance for security improvements, allowing organizations to efficiently implement changes based on automated analysis results and track their security posture over time.
Data Source
AI summary
An apparatus and method for determining a recommended cyber-attack security action are provided. The apparatus includes a processor and a memory communicatively coupled to the at least a processor. The memory contains instructions configuring the at least a processor to receive a cyber profile associated with a digital environment. The processor is further configured to receive a risk profile associated with the cyber profile and determine at least one security action based on the risk profile. In addition, the processor is configured to generating a user interface data structure configured to display the determined at least one security action.