2026-04-21T03:43:14Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/58582024-03-04T13:51:13Zcom_20.500.11984_473col_20.500.11984_478

Improving fuzzing assessment methods through the analysis of metrics and experimental conditions Iturbe, Mikel Eceiza Olaizola, Maialen Flores, José Luis fuzzing Evaluation methodology security software testing Metrics Fuzzing is nowadays one of the most widely used bug hunting techniques. By automatically generating malformed inputs, fuzzing aims to trigger unwanted behavior on its target. While fuzzing research has matured considerably in the last years, the evaluation and comparison of different fuzzing proposals remain challenging, as no standard set of metrics, data, or experimental conditions exist to allow such observation. This paper aims to fill that gap by proposing a standard set of features to allow such comparison. For that end, it first reviews the existing evaluation methods in the literature and discusses all existing metrics by evaluating seven fuzzers under identical experimental conditions. After examining the obtained results, it recommends a set of practices –particularly on the metrics to be used–, to allow proper comparison between different fuzzing proposals. 2022-11-17T14:16:30Z 2022-11-17T14:16:30Z 2023 http://purl.org/coar/resource_type/c_6501 0167-4048 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=169706 https://hdl.handle.net/20.500.11984/5858 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2022 The Authors Elsevier