Dynamic Microservice Security Based on Predicted Data Flow
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Solution Overview
Problem
In cloud-based computing environments, applying security measures to confidential data across multiple microservices consumes significant computational resources, particularly for data with higher levels of confidentiality, as existing methods do not efficiently manage security levels based on the predicted flow of data.
Innovation Solution
A system that retrieves user-specific microservice chains and time stamps to dynamically implement security measures corresponding to the level of confidentiality, increasing security when confidential data is predicted to be transmitted and reducing resources when it is not, by leveraging a security measure mapping and implementation module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If increased security measures are applied to data items with higher levels of confidentiality, then protection from unauthorized access is improved, but computational resources consumed increase
Solution Approach 1:
The security measure level is dynamically adjusted based on the predicted flow of confidential data. The system transitions from static security application to dynamic security adaptation, where security measures are intensified when confidential data is predicted to flow through microservices and relaxed when data flow is not predicted, thereby optimizing the balance between data protection and computational resource consumption
Solution Approach 2:
The system performs preliminary analysis to predict when confidential data will flow through microservices chains. By anticipating future data flow patterns and pre-adjusting security measures accordingly, the system avoids reactive security adjustments and achieves more efficient resource allocation, applying high security measures only when needed based on predicted data flow
2Reliability
If security measures are applied continuously to all microservices, then data protection is maintained, but computational resources are wasted when no confidential data is transmitted
Solution Approach 1:
Instead of continuous security application, the system implements periodic security measures triggered by predicted data flow events. Security measures are activated during specific time periods when confidential data is expected to flow and deactivated during periods when data flow is not predicted, transforming continuous security into periodic, event-driven security that balances protection with resource efficiency
Solution Approach 2:
The system continuously monitors actual data flow patterns and uses this feedback to refine predictions about future data flow. This feedback mechanism allows the system to improve its accuracy in predicting when confidential data will flow, thereby more precisely controlling when security measures should be applied, optimizing both protection and resource utilization
Data Source
AI summary
A method for protecting data from a user that traverses through a chain of microservices include retrieving information identifying the chain of microservices associated with a user identifier of the user and a time when the user provided data to the chain of microservices. A level of confidentiality stored in association with the user identifier and with the time is retrieved. One or more security measures corresponding to the stored level of confidentiality are implemented for each microservice of the chain of microservices during the time.