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AuthorKleber, Stephandc.contributor.author
AuthorKargl, Frankdc.contributor.author
Date of accession2020-02-21T14:34:49Zdc.date.accessioned
Available in OPARU since2020-02-21T14:34:49Zdc.date.available
Date of first publication2019-11dc.date.issued
AbstractExisting approaches to reverse engineer network protocols based on traffic traces lack comprehensive methods to determine the data type, e. g. float, timestamp, or addresses, of segments in messages of binary protocols. We propose a novel method for the analysis of unknown protocol messages to reveal the data types contained in these messages. Therefore, we split messages into segments of bytes and interpret these as vectors of byte values. Based on the vector interpretation, we can determine similarities and characteristics of specific data types. These can be used to classify segments into clusters of the same type and to identify their data type for previously trained data types. We performed first evaluations of different applications of our method that show promising results up the a data-type-recognition precision of 100 %.dc.description.abstract
Languageen_USdc.language.iso
PublisherUniversität Ulmdc.publisher
LicenseStandarddc.rights
Link to license texthttps://oparu.uni-ulm.de/xmlui/license_v3dc.rights.uri
KeywordProtocol testing and verificationdc.subject
Dewey Decimal GroupDDC 004 / Data processing & computer sciencedc.subject.ddc
LCSHElectronic data processing; Backup processing alternativesdc.subject.lcsh
LCSHIPSec (Computer network protocol)dc.subject.lcsh
LCSHComputer networksdc.subject.lcsh
LCSHComputer network protocolsdc.subject.lcsh
LCSHEvaluationdc.subject.lcsh
LCSHCluster analysisdc.subject.lcsh
LCSHComputer networks; Security measuresdc.subject.lcsh
TitlePoster: Network message field type recognitiondc.title
Resource typeBeitrag zu einer Konferenzdc.type
VersionacceptedVersiondc.description.version
DOIhttp://dx.doi.org/10.18725/OPARU-25469dc.identifier.doi
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-oparu-25532-3dc.identifier.urn
GNDDatensicherungdc.subject.gnd
GNDIPSecdc.subject.gnd
GNDDatennetzdc.subject.gnd
GNDEvaluationdc.subject.gnd
GNDComputersicherheitdc.subject.gnd
GNDCluster-Analysedc.subject.gnd
FacultyFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.affiliationGeneral
InstitutionInstitut für Verteilte Systemeuulm.affiliationSpecific
Peer reviewjauulm.peerReview
DCMI TypeTextuulm.typeDCMI
CategoryPublikationenuulm.category
DOI of original publication10.1145/3319535.3363261dc.relation1.doi
Source - Title of sourceCCS '19: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Securitysource.title
Quellenangabe - HerausgeberACMsource.contributor.editor1
Source - PublisherNew Yorksource.publisherPlace
Source - Place of publicationAssociation for Computing Machinerysource.publisher
Source - Volume2019source.volume
Source - Year2019source.year
Source - From page2581source.fromPage
Source - To page2583source.toPage
Source - ISBN978-1-4503-6747-9source.identifier.isbn
Conference name2019 ACM SIGSAC Conference on Computer and Communications Securityuulm.conferenceName
Conference placeLondonuulm.conferencePlace
Conference start date2019-11-11uulm.conferenceStartDate
Conference end date2019-11-15uulm.conferenceEndDate
Bibliographyuulmuulm.bibliographie


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