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DTLS-Fuzzer: A DTLS Protocol State Fuzzer
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.ORCID iD: 0000-0002-5185-0035
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.ORCID iD: 0000-0001-9657-0179
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
2022 (English)In: 2022 IEEE 15th International Conference on Software Testing, Verification and Validation (ICST 2022), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 456-458Conference paper, Published paper (Refereed)
Abstract [en]

DTLS-Fuzzer is a protocol state fuzzer for implementations of DTLS clients and servers. DTLS-Fuzzer uses model learning to generate a stale machine model of a DTLS implementation, capturing its input/output behavior. This model can be used for model-based testing or can be analyzed for security vulnerabilities and specification violations. This demo abstract overviews the architecture, API, and usage of the tool.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022. p. 456-458
Series
IEEE International Conference on Software Testing Verification and Validation, ISSN 2159-4848, E-ISSN 2381-2834
Keywords [en]
model learning, network security testing, model-based testing
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-484739DOI: 10.1109/ICST53961.2022.00051ISI: 000850246600041ISBN: 978-1-6654-6679-0 (electronic)ISBN: 978-1-6654-6680-6 (print)OAI: oai:DiVA.org:uu-484739DiVA, id: diva2:1696636
Conference
15th IEEE International Conference on Software Testing, Verification and Validation (ICST), APR 04-13, 2022, ELECTR NETWORK
Funder
Swedish Research CouncilSwedish Foundation for Strategic ResearchKnut and Alice Wallenberg FoundationAvailable from: 2022-09-19 Created: 2022-09-19 Last updated: 2023-08-25Bibliographically approved

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Fiterau-Brostean, PaulJonsson, BengtSagonas, KonstantinosTåquist, Fredrik

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