Graph Database Cloud Security Dependency Analysis
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Solution Overview
Problem
In cloud computing environments, existing security management systems face challenges in effectively identifying and mitigating operational or cyber risks due to the complexity of relationships between workloads and the scalability issues posed by massive amounts of network data, which can lead to breaches and data theft.
Innovation Solution
A method and system for cloud security management that involves gathering data on workloads and applications, representing them as nodes and relationships in a graph database, and using this data to identify dependencies and operational risks, enabling the creation of security policies and real-time updates to protect against threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security management systems are used to monitor cloud workloads, then security coverage is provided, but the systems cannot effectively identify operational or cyber risks due to the complexity of relationships between workloads
Solution Approach 1:
The patent introduces a graph database as an intermediary layer between traditional security systems and cloud workload relationships. This graph database models workloads, assets, and their dependencies as nodes and edges, enabling the system to handle complex relationships in a structured way that improves risk identification without being overwhelmed by complexity
Solution Approach 2:
The patent segments the complex cloud environment into discrete graph entities (nodes representing workloads/assets and edges representing relationships). This segmentation transforms the monolithic complexity of cloud relationships into manageable, queryable graph structures that can be analyzed for security risks
2Reliability
If massive amounts of network data are collected for security analysis, then comprehensive security monitoring is achieved, but scalability issues arise due to the volume of data
Solution Approach 1:
The patent extracts only the essential security-relevant relationships and workload data into a graph database structure, rather than processing all raw network data. This extraction approach maintains comprehensive security monitoring by focusing on critical dependencies while improving scalability by reducing the volume of data that requires intensive processing
Solution Approach 2:
The patent changes the data representation parameter from traditional flat or hierarchical structures to graph-based structures. This parameter change enables more efficient querying and analysis of relationships, allowing the system to scale better while maintaining comprehensive security coverage through graph traversal algorithms
3Measurement precision
If detailed relationships between workloads are mapped, then operational risks can be identified, but the system complexity and data processing requirements increase
Solution Approach 1:
The graph database serves as an intermediary that handles the complexity of detailed relationship mapping. By storing workloads, assets, and their dependencies as interconnected graph entities, the system achieves precise dependency detection while the graph database engine manages the processing complexity, separating the precision requirement from the processing burden
Data Source
AI summary
Methods and systems for managing security in a cloud computing environment are provided. Exemplary methods include: gathering data about workloads and applications in the cloud computing environment; updating a graph database using the data, the graph database representing the workloads of the cloud computing environment as nodes and relationships between the workloads as edges; receiving a security template, the security template logically describing targets in the cloud computing environment to be protected and how to protect the targets; creating a security policy using the security template and information in the graph database; and deploying the security policy in the cloud computing environment.