[Paper] MHOT: Height-Optimized Authenticated Data Structure for Blockchain State Commitment

Source: arXiv - 2606.11736v1

Overview

State root computation dominates (78%) blockchain block processing time. Ethereum’s canonical authenticated data structure, i.e., Merkle Patricia Trie (MPT), suffers from severe tree-height growth and is vulnerable to \textit{Nurgle attacks} (SP’24), where adversaries inflate path depth via hash collisions and degrade system performance at negligible cost. Existing defenses increase node fanout (span) to bound tree height, but higher span inflates proof size exponentially. Prior work mitigates this trade-off using vector commitments, at the cost of trusted setup or expensive verification. We present \textsc{Mhot}, a height-optimal authenticated data structure for blockchain state commitment that preserves standard hash-based verification without trusted setup. Unlike MPT’s fixed-prefix indexing, which couples span and fanout exponentially, \textsc{Mhot} indexes by discriminative bits that actually distinguish keys, achieving adaptive span with linear fanout coupling and provably minimal height. To prevent high fanout from inflating proofs, we introduce hierarchical proofs, a two-layer Merkle construction that reduces per-node proof overhead from O(k) to O(log k). On Ethereum mainnet workloads, \textsc{Mhot} achieves up to 9X higher write throughput, 4X lower write amplification, and 2X smaller proofs than MPT. Under Nurgle attacks, even when the adversary consumes an entire block’s gas budget, \textsc{Mhot} maintains a 0% attack success rate (v.s., 99.97% for MPT). Our results, somewhat surprisingly, show that height optimality (not new crypto primitives!) is the key abstraction for scalable and attack-resilient blockchain state commitment.

Key Contributions

This paper presents research in the following areas:

• cs.CR
• cs.DC
• cs.ET

Methodology

Please refer to the full paper for detailed methodology.

Practical Implications

This research contributes to the advancement of cs.CR.

Authors

• Sipeng Xie
• Qianhong Wu
• Minghang Li
• Qiyuan Gao
• Bo Qin
• Qin Wang

Paper Information

• arXiv ID: 2606.11736v1
• Categories: cs.CR, cs.DC, cs.ET
• Published: June 10, 2026
• PDF: Download PDF