Automated Security Score Engine for Application Vulnerability Assessment
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Solution Overview
Problem
In large distributed computing systems, identifying and remediating vulnerabilities and efficiently allocating resources to secure the system is challenging due to increasing complexity and frequent changes in services and resources, making it difficult to isolate and troubleshoot issues while ensuring compliance with various standards and regulations.
Innovation Solution
A security engine determines a security score for applications based on various data points organized into axes, using a scoring model like the Capability Maturity Model (CMM), and a security and maturity service continuously aggregates information to generate recommended security actions, leveraging statistical modeling and machine learning to adjust weights and correlations for improved security resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual security assessment methods are used, then security experts can deeply analyze individual applications, but the complexity and time required increase significantly with system scale
Solution Approach 1:
The patent segments the security assessment process into automated data collection (gathering security configuration data, vulnerability data, threat data) and automated scoring (calculating security scores based on weighted criteria). This segmentation allows systematic evaluation of multiple applications simultaneously, reducing assessment time while maintaining precision through structured analysis frameworks.
Solution Approach 2:
The patent introduces automated security assessment tools and algorithms as intermediaries between security experts and applications. These intermediaries collect security data, evaluate configurations, calculate vulnerability risks, and generate security scores, enabling scalable assessment without requiring expert manual analysis of each application while maintaining assessment quality.
2Reliability
If comprehensive security monitoring is implemented across all applications, then security risks can be identified, but the complexity of managing and analyzing data from all applications increases
Solution Approach 1:
The patent segments security data into distinct categories (security configuration data, vulnerability data, threat data) and processes each type through specialized automated algorithms. This segmentation organizes the complex data landscape, making it manageable and analyzable while maintaining comprehensive security monitoring across all applications.
Solution Approach 2:
The patent transforms complex security data into simplified security scores through automated calculation algorithms that apply weighted criteria and normalization. This parameter transformation converts multidimensional security data into comparable numerical values, reducing data management complexity while preserving reliability for risk identification and prioritization.
3Productivity
If security resources are allocated based on manual assessment, then expert judgment can be applied, but the efficiency and scalability of resource allocation decreases
Solution Approach 1:
The patent implements continuous automated security monitoring that generates security scores and feeds this information back to resource allocation decisions. The system continuously collects security data, updates security scores, and uses this feedback loop to dynamically allocate security resources to applications with higher risk scores, improving both efficiency and accuracy of resource distribution.
Solution Approach 2:
The patent enables applications to self-report security configuration data and allows the automated system to self-evaluate security postures through algorithmic analysis. This self-service approach eliminates manual assessment requirements, scaling resource allocation efficiently across numerous applications while maintaining assessment accuracy through consistent automated evaluation criteria.
Data Source
AI summary
A security and maturity service is provided to generate a security score for an application. A set of data points are obtained, the data points indicating application information for an application. The data points may be associated with a particular axis of a plurality of axes defined by a scoring model. Furthermore, the scoring model may define a score for each axes based at least in part on the data points. A security score for the application may then be determined based at least in part on the score for the plurality of axes.