Non-Cryptographic Hash Functions: Design and Evaluation

This article delves into the design and evaluation of non-cryptographic hash functions. By analyzing the performance of common functions like FNV-1a, FNV-1, Murmur2, and DJBX33A on diverse datasets (including names, words, IP addresses, and a deliberately biased dataset), the authors reveal key characteristics such as uniformity, collision rate, and avalanche effect. Experiments show Murmur2 excels in the avalanche effect but isn't always optimal for uniformity. The article stresses the importance of dataset characteristics in choosing appropriate hash functions and questions existing evaluation criteria, arguing that a single metric (like the avalanche effect) is insufficient for comprehensively assessing non-cryptographic hash function performance.