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Finding a needle in a haystack: A comparative study of IPv6 scanning methods
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-2015-9185
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2019 (English)In: 2019 INTERNATIONAL SYMPOSIUM ON NETWORKS, COMPUTERS AND COMMUNICATIONS (ISNCC 2019), IEEE, 2019Conference paper, Published paper (Refereed)
Abstract [en]

It has previously been assumed that the size of anIPv6 network would make it impossible to scan the network forvulnerable hosts. Recent work has shown this to be false, andseveral methods for scanning IPv6 networks have been suggested.However, most of these are based on external information likeDNS, or pattern inference which requires large amounts of knownIP addresses. In this paper, DeHCP, a novel approach based ondelimiting IP ranges with closely clustered hosts, is presentedand compared to three previously known scanning methods. Themethod is shown to work in an experimental setting with resultscomparable to that of the previously suggested methods, and isalso shown to have the advantage of not being limited to a specificprotocol or probing method. Finally we show that the scan canbe executed across multiple VLANs.

Place, publisher, year, edition, pages
IEEE, 2019.
Keywords [en]
ipv6, ipv6 scanning, cyber scanning, host discovery, penetration testing
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:bth-18901DOI: 10.1109/ISNCC.2019.8909131ISI: 000520478600045ISBN: 9781728112435 (print)OAI: oai:DiVA.org:bth-18901DiVA, id: diva2:1369624
Conference
6th IEEE Int. Symposium on Networks, Computer and Communication, , 18-20 June, Istanbul
Part of project
Bigdata@BTH- Scalable resource-efficient systems for big data analytics, Knowledge Foundation
Note

open access

Available from: 2019-11-12 Created: 2019-11-12 Last updated: 2021-10-07Bibliographically approved

Open Access in DiVA

isncc2019-ipv6(252 kB)419 downloads
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045382f62675344753663e52e2dd3f2ea23f2f86a7f1b32a049e6e702cd6162a90f7992724dc46496c899930c87f2941bad1b30e4b21740fc801014b727a9598
Type fulltextMimetype application/pdf

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Bergenholtz, ErikMoss, AndrewIlie, DragosCasalicchio, Emiliano

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