Private Infrastructure Evidence Collection via Secure Agent Tunnels
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Solution Overview
Problem
Current techniques for collecting compliance evidence from closed, private computing infrastructures are manual, static, and fail to capture the dynamic nature of organizational growth and compliance changes, especially in hybrid and cloud environments, posing security risks due to complex firewall configurations.
Innovation Solution
Establishing a secure tunnel through an agent deployed in the tenant cloud to access closed user systems, using dedicated ports and private keys for secure and continuous evidence collection, avoiding firewall configurations and ensuring tenant-controlled access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evidence collection techniques are used, then implementation simplicity is maintained, but compliance accuracy and timeliness deteriorate due to static nature and inability to capture dynamic organizational changes
Solution Approach 1:
The patent introduces an agent as an intermediary component deployed within the private infrastructure that mediates between the evidence collector and the user systems. This agent automatically discovers user systems, manages secure tunnel connections, and facilitates continuous evidence collection without requiring complex manual configuration, thereby improving compliance accuracy while managing system complexity.
Solution Approach 2:
The agent implements self-service capabilities by automatically discovering user systems within the private infrastructure, autonomously establishing secure tunnel connections, and continuously monitoring for changes. This automation eliminates the need for manual intervention in evidence collection processes, improving both accuracy and timeliness while reducing operational complexity.
2Reliability
If secure tunnels are established through agent in tenant cloud, then security and accessibility are improved for closed infrastructures, but device complexity increases due to tunnel management requirements
Solution Approach 1:
The agent autonomously manages the secure tunnel lifecycle including automatic establishment, maintenance, and termination of tunnels. It self-configures connection parameters, handles authentication credentials, and adapts to network changes without requiring manual tunnel management, thereby improving security while reducing the operational complexity of tunnel management.
Solution Approach 2:
The system implements feedback mechanisms where the agent continuously monitors the state of secure tunnels and automatically adjusts connections based on detected changes in the private infrastructure. This feedback loop ensures reliable secure access while simplifying tunnel management by eliminating the need for manual monitoring and adjustment.
3Loss of time
If continuous evidence collection is implemented through automatic tunnel establishment, then compliance timeliness is improved, but use of energy and computational resources increases
Solution Approach 1:
The system implements periodic evidence collection through the agent rather than continuous collection. The agent establishes secure tunnels and collects evidence at scheduled intervals, automatically adapting the collection frequency based on compliance requirements and detected changes in the infrastructure. This periodic approach improves compliance timeliness while significantly reducing computational resource consumption compared to continuous collection.
Solution Approach 2:
The evidence collection system dynamically adjusts its operation based on detected changes in the private infrastructure. When changes are detected, the agent increases collection frequency to maintain compliance timeliness. When no changes are detected, the system reduces collection activity to minimize computational resource consumption, achieving an optimal balance between timeliness and resource usage.
Data Source
AI summary
A system and method for collecting evidence from a private computing infrastructure is provided. The method includes establishing at least one secure tunnel with a user system of the private computing infrastructure through an agent; initiating an evidence collection over the at least one secure tunnel, wherein initiating the evidence collection further comprises fetching tunnel details; accessing the user system via a first tunnel of the least one secure tunnel, wherein the first tunnel is active and identified from the fetched tunnel details; and collecting raw data of evidence from the user system.