Cybersecurity Scoring Framework for Heterogeneous Risk Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cybersecurity assessment methods fail to generate comprehensive cybersecurity scores due to heterogeneous data sources with varying data content, format, timespan, and scale, lacking time-graphs and holistic reconnaissance, which impedes effective security profiling and cost-benefit analysis for network security adjustments.
Innovation Solution
A system and method for self-adjusting cybersecurity analysis that gathers, evaluates, and weights various cybersecurity aspects from a client's network and internet data, generating a comprehensive score using a transparent methodology, and adjusts security levels based on a score set point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive data gathering from multiple heterogeneous sources is implemented, then measurement precision of cybersecurity assessment is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system segments the cybersecurity assessment into multiple independent aspects (e.g., network security, application security, device security) that can be evaluated separately. Each aspect is scored independently and then aggregated to form the comprehensive cybersecurity score, making the complex assessment manageable and systematic.
Solution Approach 2:
The patent introduces a standardized scoring framework as an intermediary layer between heterogeneous data sources and the final cybersecurity assessment. This framework normalizes diverse data formats and sources into a unified scoring system, enabling accurate comparison and aggregation without requiring direct integration of all raw data sources.
2Reliability
If extensive data collection and holistic reconnaissance are performed, then reliability of cybersecurity profiling is improved, but loss of time and processing resources increase
Solution Approach 1:
The system performs preliminary data collection and normalization activities in advance, establishing a baseline cybersecurity profile that can be quickly updated. Reconnaissance activities are structured to gather essential information first, with optional deeper analysis available when needed, reducing the time required for routine assessments.
Solution Approach 2:
The cybersecurity assessment is designed to be performed periodically at scheduled intervals, allowing the system to maintain current security profiles without requiring continuous monitoring. Between periodic assessments, the system can operate with updated baseline data, reducing overall processing time while maintaining reliability.
3Loss of information
If multiple data sources with varying formats and timespans are integrated, then comprehensiveness of security assessment is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The system transforms heterogeneous data from multiple sources by changing their parameters to a standardized format. Different data types, formats, and timespans are converted into a common scoring parameter structure, enabling consistent measurement and comparison across all data sources while preserving the underlying information.
Solution Approach 2:
The patent creates a universal scoring framework that can accommodate multiple data sources with varying formats and characteristics. This multi-functional system handles different types of cybersecurity data (network, application, device, human elements) through a single integrated assessment methodology, simplifying the integration process.
Data Source
AI summary
A reconnaissance engine gathers data about a client's computer network from the client, from devices and systems on the client's network, and from the Internet regarding various aspects of cybersecurity. Each of these aspects is evaluated independently, weighted, and cross-referenced to generate a cybersecurity score by aggregating individual vulnerability and risk factors together to provide a comprehensive characterization of cybersecurity risk using a transparent and traceable methodology. The scoring system itself can be used as a state machine with the cybersecurity score acting as a feedback mechanism, in which a cybersecurity score can be set at a level appropriate for a given organization, and data from clients or groups of clients with more extensive reporting can be used to supplement data for clients or groups of clients with less extensive reporting to enhance cybersecurity analysis and scoring.