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dc.contributor.advisorConklin, Wm. Arthur
dc.creatorJain, Utkarsh
dc.date.accessioned2018-06-22T21:52:52Z
dc.date.available2018-06-22T21:52:52Z
dc.date.createdMay 2018
dc.date.issued2018-05
dc.date.submittedMay 2018
dc.identifier.urihttp://hdl.handle.net/10657/3109
dc.description.abstractIn recent time, it is becoming increasingly difficult to prevent initial infiltration of a network, making it important to always consider and improve detection of an ongoing incident. Any attacker spends most energy, time and is additionally the most defenseless against detection when the attacker is trying to move laterally from system to system to escalate privileges. This research takes into consideration, majority of tools and techniques used by adversaries to move in a windows-based network laterally. It showcases the execution of these tools and suggests how usage of such tools can be detected using logging. Hence, this research is an attempt at creating a solution which helps in detection of lateral movement happening inside a windows-based network by collecting logs and analyzing them using ELK stack as the logging tool.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectLateral Movement
dc.subjectELK stack
dc.subjectLateral movement detection
dc.titleLateral Movement Detection Using ELK Stack
dc.date.updated2018-06-22T21:52:52Z
dc.type.genreThesis
thesis.degree.nameMaster of Science
thesis.degree.levelMasters
thesis.degree.disciplineInformation Systems Security
thesis.degree.grantorUniversity of Houston
thesis.degree.departmentInformation and Logistics Technology, Department of
dc.contributor.committeeMemberBronk, Chris
dc.contributor.committeeMemberKinsey, Denise M.
dc.type.dcmiText
dc.format.digitalOriginborn digital
dc.description.departmentInformation and Logistics Technology, Department of
thesis.degree.collegeCollege of Technology


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