Experiment Data for MoonLight: Effective Fuzzing with Near-Optimal Corpus Distillation

TypeCollection
TitleExperiment Data for MoonLight: Effective Fuzzing with Near-Optimal Corpus Distillation
Brief TitleMoonLight Experiment Data
Collection TypeDataset
Access PrivilegesResearch School of Computer Science
DOI - Digital Object Identifier10.25911/5c92feecbf225
Metadata LanguageEnglish
Data LanguageEnglish
Full DescriptionExperiment data for MoonLight: Effective Fuzzing with Near-Optimal Corpus Distillation. This includes the statistic, queue and crashes for each individual fuzzers. There are 7 targets (Poppler - PDF, SoX - MP3, SoX - WAV, librsvg - SVG, libtiff - TIFF, FreeType - TTF, and libxml2 - XML), 30 experiments each, comparing against 6 approaches (empty, full, afl-cmin, moonlight-U, moonlight-S, moonlight-T)
Contact Emailhendra.gunadi@anu.edu.au
Contact AddressThe Australian National University,
College of Engineering and Computer Science,
CSIT Building,
108 North Rd, Acton, ACT,
Australia
Principal InvestigatorHendra Gunadi
SupervisorsAntony L. Hosking
Michael Norrish
Shane Magrath
Adrian Herrera
CollaboratorsLiam Hayes
Jonathon Milford
Maggi Sebastian
Fields of Research080303 - Computer System Security
Keywordsfuzzing
corpus distillation
Type of Research ActivityExperimental development
Date of data creation2018
Year of data publication2019
Creator(s) for Citation
Given NameSurname
HendraGunadi
Publisher for CitationThe Australian National University Data Commons
Related Websites
URLTitle
https://gitlab.anu.edu.au/lunarMoonLight and MoonBeam
Access Rights TypeOpen
Rights held in and over the dataCreative Commons Licence (CC BY) is assigned to this data. Details of the licence can be found at http://creativecommons.org.au/licences.
Licence TypeCC-BY - Attribution (Version 4)
Retention PeriodIndefinitely
Extent or Quantity1278 files
Data Size39.5 GB
Data Management PlanNo
Status: Published
Published To:
- Australian National University
- Australian National Data Service
Identifier: anudc:5927
Related Items
Files

Estimates:

  • Files: 3686
  • Size: 948 GB

Data Files

Updated:  07 February 2019/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator