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dc.contributor.authorStefan, Deianen
dc.contributor.authorYao, Danfeng (Daphne)en
dc.date.accessioned2018-07-19T16:54:24Zen
dc.date.available2018-07-19T16:54:24Zen
dc.date.issued2010en
dc.identifier.urihttp://hdl.handle.net/10919/84196en
dc.description.abstractWe describe the use of keystroke-dynamics patterns for authentication and detecting infected hosts, and evaluate its robustness against forgery attacks. Specifically, we present a remote authentication framework called TUBA for monitoring a user’s typing patterns. We evaluate the robustness of TUBA through comprehensive experimental evaluation including two series of simulated bots. Support vector machine is used for classification. Our results based on 20 users’ keystroke data are reported. Our work shows that keystroke dynamics is robust against synthetic forgery attacks studied, where attacker draws statistical samples from a pool of available keystroke datasets other than the target. TUBA is particularly suitable for detecting extrusion in organizations and protecting the integrity of hosts in collaborative environments, as well as authentication.en
dc.description.sponsorshipThis work has been supported in part by Rutgers DIMACS REU programs, National Science Foundation grants CNS-0831186 and CAREER CNS- 0953638.en
dc.language.isoen_USen
dc.publisherIEEEen
dc.relation.ispartofProceedings of the 6th International {ICST} Conference on Collaborative Computing: Networking, Applications,Worksharingen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectKeystroke dynamicsen
dc.subjectauthenticationen
dc.subjectmalware detectionen
dc.subjectforgeryen
dc.titleKeystroke-Dynamics Authentication Against Synthetic Forgeriesen
dc.typeConference proceedingen
dc.typePresentationen
dc.contributor.departmentComputer Scienceen
dc.identifier.doihttps://doi.org/10.4108/icst.collaboratecom.2010.16en


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