# PubSub-SGX: Exploiting Trusted Execution Environments for Privacy-Preserving Publish/Subscribe Systems

## TL;DR

PUBSUB-SGX leverages trusted execution environments like Intel SGX to create a privacy-preserving publish-subscribe system, ensuring data confidentiality, integrity, and user anonymity, with a focus on implementation and performance trade-offs.

## Contribution

The paper introduces PUBSUB-SGX, a novel content-based publish-subscribe system utilizing TEEs for enhanced privacy and security, including a Python implementation and deployment in container environments.

## Key findings

- Python inside TEEs can be faster than native execution due to just-in-time compilation.
- The system guarantees data confidentiality and user privacy in publish-subscribe communications.
- Performance and scalability trade-offs are identified and analyzed.

## Abstract

This paper presents PUBSUB-SGX, a content-based publish-subscribe system that exploits trusted execution environments (TEEs), such as Intel SGX, to guarantee confidentiality and integrity of data as well as anonymity and privacy of publishers and subscribers. We describe the technical details of our Python implementation, as well as the required system support introduced to deploy our system in a container-based runtime. Our evaluation results show that our approach is sound, while at the same time highlighting the performance and scalability trade-offs. In particular, by supporting just-in-time compilation inside of TEEs, Python programs inside of TEEs are in general faster than when executed natively using standard CPython.