Security Data Aggregation for Dispersed Asset Risk Management
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Solution Overview
Problem
Global companies face challenges in managing and securing geographically dispersed computing assets due to security risks and the need for real-time monitoring and control across multiple locations, exacerbated by the global reach of the Internet and potential hacking threats.
Innovation Solution
A system and method for aggregating and analyzing security data from multiple assets to compute metrics, generate aggregate scores, and provide risk reduction recommendations, utilizing normalization, weighting, and change effort estimates to prioritize security improvements across the assets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring and control of geographically dispersed computing assets is implemented, then security management capability is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the monitoring system into distributed agents deployed at various computing assets and a centralized server. Each agent independently collects and processes local security data, then transmits aggregated information to the server. This segmentation reduces the complexity burden on any single component while maintaining comprehensive security oversight across geographically dispersed assets.
Solution Approach 2:
The patent introduces intermediate aggregation layers that collect data from multiple sources before transmitting to the central server. These intermediaries process and summarize security information locally, reducing the data volume and processing requirements for the central system while maintaining real-time monitoring capabilities across distributed assets.
2Measurement precision
If comprehensive security data collection from multiple assets is performed, then security analysis accuracy is improved, but data processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary data processing and aggregation at distributed agents before transmission to the central server. Security events are pre-filtered, categorized, and summarized locally, so that only relevant aggregated data requires central processing. This preliminary action maintains comprehensive security analysis accuracy while significantly reducing the time and computational resources needed at the central system.
Solution Approach 2:
The patent applies different processing levels to different data types, performing comprehensive analysis on critical security events while using summary statistics for routine monitoring data. This selective processing approach maintains high accuracy for security-critical decisions while reducing overall processing time and computational resource requirements.
Data Source
AI summary
A system and method are provided for managing data, such as for example security or other business data. For the example of security data, security data is received from a plurality of assets that may or may not be remotely located. A plurality of security metrics are computed and normalized according to thresholds. Security metrics are aggregated to generate an aggregate score, this may include weighting the metrics according to metric priorities. A change effort corresponding to each metric is also received and a corresponding change effort for the aggregate score is calculated. Aggregate scores and aggregate change efforts are analyzed to generate risk reduction recommendations. Upon instruction, metrics corresponding to an aggregate score may be displayed including recommendations of metrics for risk reduction. The recommended metrics may be selected according to analysis of change-to-effort ratios for the metrics.