Multi-Layer Access Policy Enforcement Using eBPF in Multi-Tenant Clouds
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Solution Overview
Problem
In multi-tenant cloud environments, existing role-based access control techniques fail to provide adequate data security and privacy, leading to vulnerabilities and cyberattacks due to compromised administrative privileges and flawed access control policies, especially at the application and kernel levels.
Innovation Solution
Implementing an advanced multi-layer access control policy that maps and validates access control policies at both the application and kernel levels, using an eBPF program to analyze data packets, generate rules, and enforce policies to identify and prevent data vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If role-based access control techniques are used in multi-tenant cloud environments, then ease of operation is improved, but data security and reliability deteriorate due to compromised administrative privileges and flawed access control policies
Solution Approach 1:
The access control system is segmented into multiple layers: application layer policies and kernel layer policies. This segmentation allows different security enforcement points to work together, preventing single-point compromises from affecting overall system security while maintaining ease of operation through hierarchical policy management.
Solution Approach 2:
An eBPF-based intermediary component is introduced between the application layer and kernel layer to enforce access control policies. This intermediary validates data packets and enforces policies without requiring changes to existing applications or kernel code, maintaining ease of operation while improving reliability through additional security validation.
2Reliability
If multi-layer access control policy enforcement is implemented, then data security and reliability are improved, but device complexity increases due to multiple validation layers and policy mapping requirements
Solution Approach 1:
The eBPF program serves multiple functions: it validates data packets, enforces access control policies, maps application layer policies to kernel layer policies, and provides security validation. This multi-functionality reduces the need for separate components for each task, thereby reducing overall system complexity while maintaining multi-layer security.
Solution Approach 2:
The system changes the parameter of policy enforcement from application-level only to include kernel-level parameters as well. By modifying the enforcement point to include lower-level system parameters, the system achieves deeper security validation without proportionally increasing complexity, as the same eBPF infrastructure handles both application and kernel policy enforcement.
3Measurement precision
If eBPF program is used to analyze data packets and enforce policies, then measurement precision and data security are improved, but use of energy and computational resources increases
Solution Approach 1:
The eBPF program performs partial analysis of data packets by focusing only on critical security-relevant fields rather than complete packet inspection. This selective validation approach maintains high measurement precision for security decisions while reducing overall computational energy consumption compared to full packet analysis.
Data Source
AI summary
An approach is provided for multi-layer access control policy enforcement in a multi-tenant cloud environment. An advanced policy service is defined in a data container The advanced policy service provides management and validation of an access control policy at multiple levels including an application layer and a low layer, which is at a level lower than the application layer. Using the advanced policy service, a policy definition of the application layer is mapped to an access validation and authorization policy of the low layer. Rules are generated using an analysis of data packets by an eBPF program Using the eBPF program, the policy definition and the rules are applied to a request received from a SaaS application to access a data source. Based on the application of the policy definition and the rules, a data vulnerability is identified and the request is rejected.