Efficiency Without Security Trade-off: Statistically Validated Cryptographic Hash Selection for Ethereum Fraud Detection - Ahmad Dani; Wildanil Ghozi; Ramadhan Rakhmat Sani; Fauzi Adi Rafrastara (Journal of Applied Informatics and Computing, 2026)
Cryptographic hash functions form the preprocessing layer of Ethereum fraud detection pipelines, yet prior research evaluated hash performance and fraud detection as separate concerns, leaving practitioners without evidence-based guidance for selecting an algorithm that balances speed, energy efficiency, and cryptographic security. This study benchmarks SHA-256, SHA3-256, BLAKE2s-256, and BLAKE3 on a stratified sample of 6,396 fraud-labeled transactions from a public 9,841-record Ethereum dataset, measuring execution time, throughput, energy consumption, and avalanche effect. Its novelty is, to the best of our knowledge, the first inferential validation, on real fraud-labeled data, that the four algorithms are cryptographically equivalent in diffusion strength—combining non-parametric testing (Shapiro-Wilk, Mann-Whitney U, Kruskal-Wallis) with formal two one-sided equivalence tests (TOST) and replicating the result on an independent 454,289-transaction dataset—establishing that selection can be decided on efficiency grounds alone without sacrificing security. BLAKE2s-256 achieved the lowest execution time (0.65 µs), highest throughput (≈1.54 million ops/s), and lowest energy (0.029 mJ/op), while all algorithms converged near the 50% avalanche ideal with no significant security difference (H = 3.03, p = 0.387). BLAKE2s-256 attained the highest composite score (99.98/100) and, in an end-to-end pipeline test, improved batch screening throughput by up to 11.5%, confirming it as optimal for off-chain Ethereum fraud-detection preprocessing on processors without SHA hardware acceleration.