Cybersecurity Strategy Analysis Matrix for Poly-Intelligence
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Solution Overview
Problem
There is a gap in applying business intelligence capabilities beyond the scope of any single business, lacking an established method for companies to access 'poly-intelligence'—collecting data from many companies in an industry vertical and conducting BI-like analytics to determine best practices, enterprise strategies, and specific tactics based on real-world results.
Innovation Solution
The Cybersecurity Strategy Analysis Matrix (CSAM) provides a system of systems that anonymously gathers and parameterizes cybersecurity best practices data and cyber program outcomes from multiple sources, including academic research, the open internet, and individual organizations, and performs business poly-intelligence analytics using descriptive and predictive analysis algorithms to deliver insights and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If companies conduct business intelligence analytics only within their own enterprise, then they can maintain data privacy and security, but they cannot access poly-intelligence or industry best practices from other organizations
Solution Approach 1:
The patent introduces a neutral intermediary platform that acts as a mediator between competing companies. This platform enables anonymous data sharing and collaborative analytics without requiring companies to expose their identity or proprietary information directly to competitors. The intermediary structure resolves the contradiction by providing a trusted third-party environment where data privacy is maintained while still enabling access to industry-wide intelligence.
Solution Approach 2:
The system creates anonymized copies of enterprise data that can be shared and analyzed without exposing the original proprietary information. By working with replicated, de-identified data sets rather than original data, companies can participate in poly-intelligence analytics while maintaining control over their actual proprietary assets and sensitive information.
2Loss of information
If companies share cybersecurity data anonymously across enterprises, then they can access poly-intelligence and industry best practices, but they risk losing control over their proprietary information
Solution Approach 1:
The system extracts and removes identifying information and proprietary elements from data before enabling cross-enterprise sharing. By taking out the harmful or sensitive components (company identifiers, trade secrets, proprietary algorithms) while retaining the useful analytical value, the system enables poly-intelligence access without compromising control over proprietary information.
Solution Approach 2:
Different levels of data anonymity and sharing are applied to different types of information. The system allows companies to control what aspects of their data are shared anonymously versus what remains private, enabling granular control over proprietary information while still participating in industry-wide analytics where appropriate.
3Quantity of substance
If comprehensive cybersecurity data is collected from multiple sources, then poly-intelligence analytics can be performed, but data complexity and processing requirements increase significantly
Solution Approach 1:
The patent segments the comprehensive cybersecurity data into standardized, modular components that can be processed independently. By dividing the large-scale multi-source data into structured segments with consistent formats and schemas, the system reduces processing complexity while maintaining the ability to perform comprehensive poly-intelligence analytics across all data sources.
Solution Approach 2:
The system transforms raw cybersecurity data from multiple sources by changing its parameters—standardizing formats, normalizing schemas, and converting diverse data types into a unified structure. This parameter transformation reduces the complexity of processing heterogeneous data while preserving the analytical value needed for poly-intelligence insights.
Data Source
AI summary
A business poly-intelligence application enabling the secure collection, warehousing, analysis, and reporting of manually shared and publicly sourced business strategy data is presented with systems, methods, and computer-readable media with a specific focus on crowdsourced cybersecurity strategy development.