Department of Computer Systems

Conference paper

GROCHOL David and SEKANINA Lukáš. Multiobjective Evolution of Hash Functions for High Speed Networks. In: Proceedings of the 2017 IEEE Congress on Evolutionary Computation. San Sebastian: IEEE Computer Society, 2017, pp. 1533-1540. ISBN 978-1-5090-4600-3.
Publication language:english
Original title:Multiobjective Evolution of Hash Functions for High Speed Networks
Title (cs):Více-kriteriální návrh hašovacích funkcí pro vysokorychlostní sítě
Proceedings:Proceedings of the 2017 IEEE Congress on Evolutionary Computation
Conference:IEEE Congress on Evolutionary Computation 2017
Place:San Sebastian, ES
Publisher:IEEE Computer Society
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NSGA-II, linear genetic programming, hash function, network
Hashing is a critical function in capturing and analysis of network flows as its quality and execution time influences the maximum throughput of network monitoring devices. In this paper, we propose a multi-objective linear genetic programming approach to evolve fast and high-quality hash functions for common processors. The search algorithm simultaneously optimizes the quality of hashing and the execution time. As it is very time consuming to obtain the real execution time for a candidate solution on a particular processor, the execution time is estimated in the fitness function. In order to demonstrate the superiority of the proposed approach, evolved hash functions are compared with hash functions available in the literature using real-world network data.
   author = {David Grochol and Luk{\'{a}}{\v{s}} Sekanina},
   title = {Multiobjective Evolution of Hash Functions for High Speed
   pages = {1533--1540},
   booktitle = {Proceedings of the 2017 IEEE Congress on Evolutionary
   year = {2017},
   location = {San Sebastian, ES},
   publisher = {IEEE Computer Society},
   ISBN = {978-1-5090-4600-3},
   language = {english},
   url = {}

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