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dc.contributor.advisorMonaco, John
dc.contributor.authorVerkempinck, Jeana M.
dc.contributor.authorArnell, Alexander
dc.contributor.authorBullock, Cassondra C.
dc.date.accessioned2020-08-21T00:25:05Z
dc.date.available2020-08-21T00:25:05Z
dc.date.issued2020-06
dc.identifier.urihttp://hdl.handle.net/10945/65459
dc.description.abstractInstant Message (IM) applications are commonly used by both civilian and DoD personnel for both communication and collaboration. The web-based variants of these applications generally ride encrypted channels for message security. However, these channels may be vulnerable to keystroke timing attacks whereby textual content is determined by the timing of network traffic induced by keyboard events. An example of this induced traffic is the activity notifications common to many of these platforms, indicating when a conversant begins typing. Our aim is to determine whether the network traffic that carries this metadata enables recovering portions of the message or leaks information about the sender's identity. Using a combination of network packet capture analysis and local keystroke logging, we characterize traffic patterns of three widely used web-based IM platforms: Facebook Messaging, Google Hangouts, and Internet Relay Chat (IRC) through the Kiwi IRC web client.en_US
dc.publisherMonterey, CA; Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleINSTANT MESSAGE TRAFFIC META-DATA AND ITS SUSCEPTIBILITY TO TRAFFIC ANALYSISen_US
dc.typeThesisen_US
dc.contributor.secondreaderBeverly, Robert
dc.contributor.departmentInformation Sciences (IS)
dc.contributor.departmentInformation Sciences (IS)
dc.contributor.departmentInformation Sciences (IS)
dc.subject.authormeta-dataen_US
dc.subject.authorchaten_US
dc.subject.authorInstant Messageen_US
dc.subject.authorvulnerabilitiesen_US
dc.subject.authorFacebooken_US
dc.subject.authorMicrosoft Teamsen_US
dc.subject.authornetwork traffic analysisen_US
dc.subject.authorcovert channelsen_US
dc.subject.authordata exfiltrationen_US
dc.description.servicePetty Officer First Class, United States Navyen_US
dc.description.servicePetty Officer First Class, United States Navyen_US
dc.description.serviceChief Petty Officer, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Applied Cyber Operationsen_US
etd.thesisdegree.nameMaster of Science in Applied Cyber Operationsen_US
etd.thesisdegree.nameMaster of Science in Applied Cyber Operationsen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineApplied Cyber Operationsen_US
etd.thesisdegree.disciplineApplied Cyber Operationsen_US
etd.thesisdegree.disciplineApplied Cyber Operationsen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.identifier.thesisid34394
dc.description.distributionstatementApproved for public release. distribution is unlimiteden_US


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