Graph Database Universal Data Format Security Analysis
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Solution Overview
Problem
Large software systems with disparate platforms face inefficiencies and security vulnerabilities due to complex access management and incompatible data formats, leading to difficulties in identifying and mitigating security risks across multiple platforms.
Innovation Solution
The system transforms data objects from disparate formats into a universal format using a graph database, enabling centralized analysis and identifying relationships between objects to enforce system-wide security and manage access permissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention and audits are used to analyze security information across multiple platforms, then security risks can be identified, but the process is time-consuming and complex due to incompatible data formats and disconnected systems
Solution Approach 1:
The patent introduces an intermediary system that includes a data lake and processing engine to transform and standardize data from multiple disparate sources into a common format, enabling automated security analysis without manual intervention across incompatible systems
Solution Approach 2:
The patent replaces manual security auditing processes with an automated computational system that uses machine learning models and processing engines to analyze security risks across multiple platforms without human intervention
2Adaptability or versatility
If data is stored in disparate formats across multiple source systems, then each system can maintain its own data structure, but cross-platform analysis and relationship identification become difficult
Solution Approach 1:
The patent creates a universal data lake that can store and process data from multiple different source systems in their native formats while providing a standardized interface for cross-platform analysis, achieving both system independence and data compatibility
Solution Approach 2:
The patent segments the data architecture into separate components: source systems that maintain their own formats, a transformation layer that standardizes data, and an analysis layer that performs cross-platform security analysis, allowing each component to operate independently
3Productivity
If security audits are performed infrequently due to manual process complexity, then system operations are less disrupted, but security vulnerabilities remain undetected for longer periods
Solution Approach 1:
The patent implements continuous automated security monitoring and analysis that operates without interruption, continuously processing data from multiple sources and identifying security risks in real-time rather than through periodic manual audits
Data Source
AI summary
Methods and systems are disclosed for generating common objects in a universal format. A stream of data objects is received from each of a plurality of databases. Each stream of data objects includes objects represented in a disparate data type from objects in other streams. A plurality of agents are generated and configured to process data objects of a particular format. For each object, a source database of the data object is identified. An agent of the plurality of agents can be selected based on a database type of the source database. The agent generates a common object from the data object that is represented in a universal format. The common object is stored a graph database of common objects.