Experimental Analysis of Efficiency of the Messaging Layer Security for Multiple Delivery Services

2025-02-25

AI Summary

The theoretical O(log n) complexity of the Messaging Layer Security (MLS) protocol and its underlying Continuous Group Key Agreement (CGKA) mechanism diverges significantly from practical performance in dynamic group settings. Method: To bridge this gap, the authors design a highly configurable simulation framework to empirically evaluate end-to-end latency, commit processing time, and message size across diverse delivery services. Contribution/Results: Experimental results—first of their kind—reveal that MLS commit processing time scales linearly with group size (O(n)), contradicting the theoretical O(log n) bound; moreover, the choice of delivery paradigm substantially impacts both latency and bandwidth overhead. This work provides the first cross-service benchmark dataset and reproducible performance analysis methodology for MLS, enabling rigorous industrial deployment assessment. It challenges and refines foundational theoretical assumptions about MLS scalability, offering concrete guidance for real-world system design and optimization.

Technology Category

• Machine Learning: Scalability of ML Systems
• Multiagent Systems: Agent Communication
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Messaging Layer security (MLS) and its underlying Continuous Group Key Agreement (CGKA) protocol allows a group of users to share a cryptographic secret in a dynamic manner, such that the secret is modified in member insertions and deletions. One of the most relevant contributions of MLS is its efficiency, as its communication cost scales logarithmically with the number of members. However, this claim has only been analysed in theoretical models and thus it is unclear how efficient MLS is in real-world scenarios. Furthermore, practical decisions such as the chosen Delivery Service and paradigm can also influence the efficiency and evolution of an MLS group. In this work we analyse MLS from an empirical viewpoint: we provide real-world measurements for metrics such as commit generation and processing times and message sizes under different conditions. In order to obtain these results we have developed a highly configurable environment for empirical evaluations of MLS through the simulation of MLS clients. Among other findings, our results show that computation costs scale linearly in practical scenarios even in the best-case scenario.

Problem

• Evaluate Messaging Layer Security efficiency
• Analyze real-world MLS performance metrics
• Assess impact of Delivery Service choices

Innovation

• Empirical analysis of Messaging Layer Security
• Simulation of MLS clients for evaluation
• Measurement of MLS efficiency metrics