GP-hash: Automatic Generation of Non Cryptographic Hash Functions Using Genetic Programming

摘要: Non cryptographic hash functions have an immense number of important practical applications due to their powerful search properties. However, those properties critically depends on good designs: inappropriately chosen hash functions are a very common source of performance losses. On the other hand, hash functions are difficult to design: they are extremely non linear and counterintuitive, and relationships between the variables are often intricate and obscure. In this work we demonstrate the utility of Genetic Programming to automatically generate non cryptographic hashes that can compete with state of the art hash functions. We describe the design and implementation of our system, called GP-hash. Also, we experimentally identify the most proper terminal and function set, fitness function, and parameters set for this task, providing interesting information for future research in this topic. Using GP-hash, we were able to generate a non cryptographic hash, which we call gp-hash01. This hash is able to compete with a selection of the most important functions of the hashing literature, most of them widely used in the industry and created by world-class hashing experts with years of experience.