Integrating Privacy Techniques into High-Performance gRPC-based Microservice Communication

核心概念

This paper proposes a novel approach for integrating advanced privacy techniques, such as data minimization and purpose limitation, into the high-performance gRPC framework for microservice communication in a configurable and extensible manner.

要約

The paper presents a general approach and a proof-of-concept implementation for integrating privacy techniques into gRPC-based microservice communication. The key highlights are:

Motivation: Microservice architectures and gRPC are widely adopted, but lack advanced privacy techniques beyond basic transport encryption and authentication. This is problematic for fulfilling regulatory requirements around data minimization and purpose limitation.

Approach: The authors propose a server-side middleware solution implemented as a gRPC response interceptor. It separates the Policy Administration Point (PAP) and Policy Decision Point (PDP) from the Policy Enforcement Point (PEP) to minimize performance overhead. JSON Web Tokens (JWTs) are used to securely exchange access policy decisions between services.

Implementation: The authors implement the PAP/PDP and PEP components in Go. The PEP interceptor applies various data minimization techniques (suppression, generalization, noising, reduction) based on the access policy retrieved from the JWT.

Evaluation: A preliminary performance evaluation in a food delivery microservice scenario shows the approach introduces reasonable overhead in terms of latency and throughput, with the choice of data minimization techniques having a significant impact.

Limitations and Future Work: The authors identify areas for improvement, such as advanced purpose-based access control, support for streaming communication, and extension of data minimization techniques. Further performance assessments are also proposed.

Overall, the paper presents a viable solution for integrating advanced privacy techniques into real-world gRPC-based microservice architectures, enabling regulatory compliance "by design".

統計

None

引用

None

抽出されたキーインサイト

Hook-in Privacy Techniques for gRPC-based Microservice Communication

by Loui... 場所 arxiv.org 04-09-2024

https://arxiv.org/pdf/2404.05598.pdf

深掘り質問

How can the proposed approach be extended to support advanced purpose-based access control, including tree or graph structures of allowed/prohibited intended purposes, downstream usage policies, or transformation functions?

The proposed approach can be extended to support advanced purpose-based access control by enhancing the policy administration and decision components. To incorporate tree or graph structures of allowed/prohibited intended purposes, the policy format can be expanded to include hierarchical relationships between purposes. This would enable a more granular and nuanced control over access to data based on the purpose for which it is being accessed. Downstream usage policies can be integrated by introducing additional layers in the policy structure that define how data can be further utilized beyond the initial access. Transformation functions can be implemented within the policy decision component to dynamically modify data based on specific conditions or requirements, allowing for on-the-fly data transformations before it is sent to the requesting party. By incorporating these advanced features, the approach can provide a comprehensive and flexible framework for managing access control based on diverse purposes and usage scenarios.

How would be the performance impact of the policy size and the number of relevant purposes/fields in the JWT on the overall system performance?

The performance impact of the policy size and the number of relevant purposes/fields in the JWT can have a direct influence on the overall system performance. As the policy size increases, the processing time required for policy administration and decision-making may also increase, potentially leading to higher latency in enforcing access control policies. Similarly, a larger number of relevant purposes/fields in the JWT can result in more complex decision-making processes, which could further impact system performance. The computational overhead of evaluating multiple purposes and fields for each request can lead to increased response times and reduced throughput. Therefore, it is essential to carefully manage the size and complexity of policies and JWTs to maintain optimal system performance while ensuring robust access control mechanisms.

How could the reusable components be further optimized to reduce the performance overhead, especially for the more computationally intensive data minimization techniques?

To reduce the performance overhead of the reusable components, especially for computationally intensive data minimization techniques, several optimization strategies can be implemented. One approach is to introduce caching mechanisms to store previously processed data minimization results, reducing the need for repetitive computations. By caching minimized data and reusing it when similar requests are received, the overall processing time can be significantly reduced. Additionally, implementing parallel processing techniques can help distribute the computational load across multiple cores or nodes, improving the efficiency of data minimization operations. Furthermore, optimizing the algorithms used for data minimization, such as employing more efficient data structures or algorithms, can enhance the performance of these techniques. By continuously refining and optimizing the reusable components, the performance overhead associated with data minimization can be minimized, ensuring a more streamlined and efficient system operation.