Decentralized Identity in Practice: Benchmarking Latency, Cost, and Privacy

2026-01-28

AI Summary

This study addresses the lack of systematic cross-platform empirical evaluation of decentralized identifiers (DIDs) based on distributed ledgers with respect to latency, cost, and privacy. A unified experimental framework is constructed using official SDKs from Ethereum, Hedera, and the XRP Ledger to benchmark three mainstream DID schemes. The work innovatively introduces a metadata leakage score (MLS), grounded in information entropy, to quantify privacy risks, and performs normalized analyses of latency and cost by incorporating consensus intervals and native transaction fees. Results demonstrate that Hedera achieves the best overall performance across all three metrics; XRPL exhibits stable latency but higher privacy leakage; Ethereum enables efficient off-chain DID creation yet incurs substantial on-chain operation costs. These findings provide empirical guidance for selecting appropriate DID systems in practice.

Technology Category

• Search and Optimization: Distributed Search
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Decentralized Identifiers (DIDs) are increasingly deployed on distributed ledgers, yet systematic cross-platform evidence on their operational behavior remains limited. We present an empirical benchmarking study of three prominent ledger-based DID methods - Ethereum, Hedera, and XRP Ledger - using reference Software Development Kits (SDKs) under a unified experimental setup. We measure latency, transaction cost, and on-chain metadata exposure, normalizing latency by each platform's block or consensus interval and cost by its native value transfer fee. Privacy leakage is quantified using a Metadata-Leakage Score (MLS), an entropy-based measure expressed in bits per operation. Our results reveal distinct architectural trade-offs. Ethereum enables near-instant, off-chain DID creation, but incurs the highest latency and cost for on-chain lifecycle operations. XRPL delivers deterministic and stable latency with fixed, low fees, yet exhibits higher metadata leakage due to more verbose transaction payloads. Hedera achieves the lowest on-chain latency and low fees with minimal metadata leakage, while occasional variance arises from SDK-side processing and confirmation pipelines. Overall, the findings show that ledger architecture and SDK workflows play a major role in shaping DID latency, cost, and metadata exposure, complementing the effects of the underlying consensus mechanism. These results provide evidence-based insights to support informed selection and configuration of DID systems under performance and privacy constraints.

Problem

• Decentralized Identifiers
• Latency
• Transaction Cost
• Privacy Leakage
• Distributed Ledgers

Innovation

• Decentralized Identifiers
• empirical benchmarking
• Metadata-Leakage Score
• ledger architecture
• privacy leakage