Cloud Service API Risk Scoring for Security Mitigation

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Solution Overview

Problem

Existing cloud service security risk assessment methods struggle to accurately determine security risks due to incomplete analysis of API actions and varying security requirements across different cloud environments, leading to inefficiencies and reduced reliability.

Innovation Solution

A security risk analysis system that identifies and analyzes API actions using a machine learning model, determining security category information and risk scores, and generates mitigation information to enhance security and reliability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If configuration information analysis is used for security risk assessment, then the assessment process is simple, but the accuracy of security risk assessment is insufficient

Engineering Contradiction:

Improveassessment process complexityVSAvoidsecurity risk assessment accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The security risk assessment process is segmented into multiple independent analysis components: configuration information analysis, API action capability analysis, and security requirements profile analysis. Each component processes specific aspects of cloud services separately and their results are integrated to form a comprehensive security risk assessment, thereby improving accuracy without overwhelming complexity

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The assessment methodology transitions from analyzing only static configuration parameters to incorporating dynamic parameters including API action capabilities, security requirements profiles, and behavioral characteristics. This parameter expansion enables more accurate security risk assessment by capturing the actual operational state of cloud services

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If API action analysis is incorporated into security assessment, then security risk assessment accuracy is improved, but the complexity of the assessment system increases

Engineering Contradiction:

Improvesecurity risk assessment accuracyVSAvoidassessment system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The assessment system is designed with multi-functional analysis modules that can process configuration information, API actions, and security requirements through a unified framework. This universal architecture reduces system complexity by using consistent processing logic across different analysis types rather than requiring separate specialized systems for each function

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12634326B2Systems and methods for cloud service security risk assessment

Publication Date: 2026.05.19 CAPITAL ONE SERVICES LLC

AI summary

In some implementations, a system receives a request to assess security risk associated with a cloud service. The system identifies, based on the request, one or more application programming interface (API) actions associated with the cloud service. The system determines respective security category information for the one or more API actions and/or respective security risk scores for the one or more API actions. The system generates, based on the respective security category information and/or the respective security risk scores, security risk mitigation information. The system causes, based on the security risk mitigation information, one or more actions to be performed. As an example, the system may send the security risk mitigation information to a device, which may allow for presentation of the security risk mitigation information or implementation of code that is included in the security risk mitigation information.