Virtual Private Container for Secure Third-Party Analytics
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Solution Overview
Problem
Current techniques for accessing data stored in offsite repositories are insecure, leading to data leaks and vulnerabilities due to improper sanitization and authorization issues, especially when third-party analytics are involved, resulting in significant labor costs and potential data corruption.
Innovation Solution
The development of a virtual private container (VPC) that provides a self-contained software environment with isolated analytic components, an interface for user authentication, and a gateway for secure data access from external sources, with strict rules for data ingress and egress to prevent unauthorized data movement and ensure secure analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If third-party analytics tools are integrated to access customer data, then analytic capabilities are enhanced, but security risks and data leakage vulnerabilities increase
Solution Approach 1:
The system segments the analytics environment into isolated virtual containers, each dedicated to a specific customer. This segmentation allows multiple third-party analytics tools to operate simultaneously with enhanced capabilities while preventing cross-contamination and data leakage between customers, thus resolving the security risk associated with integrated analytics.
Solution Approach 2:
The patent introduces a virtual container as an intermediary layer between customer data and third-party analytics tools. This intermediary provides controlled access through defined interfaces, enabling analytics capabilities while preventing direct access to raw data, thereby maintaining data security while enhancing analytic versatility.
2Reliability
If custom data environments are manually tailored to client needs, then customer-specific security and access requirements are met, but labor costs and deployment time increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-configuring virtual container templates with standard security policies, authentication mechanisms, and access controls. When a new customer requires customized access, the system instantiates a pre-prepared template rather than building from scratch, dramatically reducing deployment time while maintaining customized security requirements through template-specific configurations.
Solution Approach 2:
The patent utilizes parameter changes by allowing virtual container templates to be instantiated with different configuration parameters for each customer (e.g., authentication methods, data access permissions, encryption settings). This enables customized security for each client without manual reconfiguration, reducing both labor costs and deployment time while maintaining reliability.
3Reliability
If virtual containers are instantiated with strict data access controls, then data leakage is prevented, but data processing flexibility and analyst access are restricted
Solution Approach 1:
The system implements dynamic data access controls within virtual containers, where access permissions can be adjusted based on the specific analytic task, user role, and data sensitivity. This dynamic approach maintains strict data protection by default while allowing flexible access when needed, resolving the contradiction between data protection and operational flexibility.
Solution Approach 2:
The virtual container architecture provides universal access control mechanisms that serve multiple functions: authentication, authorization, auditing, and data masking. This multi-functionality allows a single set of controls to both protect data and enable flexible access for legitimate analytic operations, eliminating the need to choose between protection and flexibility.
Data Source
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AI summary
Techniques for generating a virtual private container (VPC) are disclosed. In one embodiment, the techniques may be realized as a virtual container defining a self-contained software environment, comprising one or more analytic components configured to carry out specified analytic functions on data within the container, wherein the one or more analytic components are isolated to run within the self-contained software environment of the container; an interface configured to identify and authenticate a particular user and provide analysis results generated by the one or more analytic components; and a gateway configured to receive data from one or more secure data sources external to the virtual container and associated with the particular user for use by the one or more analytic components.