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dc.contributor.authorDeYoung, Mark Edwarden_US
dc.date.accessioned2018-04-25T08:00:26Z
dc.date.available2018-04-25T08:00:26Z
dc.date.issued2018-04-24
dc.identifier.othervt_gsexam:14770en_US
dc.identifier.urihttp://hdl.handle.net/10919/82909
dc.description.abstractThe problem of revealing accurate statistics about a population while maintaining privacy of individuals is extensively studied in several related disciplines. Statisticians, information security experts, and computational theory researchers, to name a few, have produced extensive bodies of work regarding privacy preservation. Still the need to improve our ability to control the dissemination of potentially private information is driven home by an incessant rhythm of data breaches, data leaks, and privacy exposure. History has shown that both public and private sector organizations are not immune to loss of control over data due to lax handling, incidental leakage, or adversarial breaches. Prudent organizations should consider the sensitive nature of network security data and network operations performance data recorded as logged events. These logged events often contain data elements that are directly correlated with sensitive information about people and their activities -- often at the same level of detail as sensor data. Privacy preserving data publication has the potential to support reproducibility and exploration of new analytic techniques for network security. Providing sanitized data sets de-couples privacy protection efforts from analytic research. De-coupling privacy protections from analytical capabilities enables specialists to tease out the information and knowledge hidden in high dimensional data, while, at the same time, providing some degree of assurance that people's private information is not exposed unnecessarily. In this research we propose methods that support a risk based approach to privacy preserving data publication for network security data. Our main research objective is the design and implementation of technical methods to support the appropriate release of network security data so it can be utilized to develop new analytic methods in an ethical manner. Our intent is to produce a database which holds network security data representative of a contextualized network and people's interaction with the network mid-points and end-points without the problems of identifiability.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectPrivacyen_US
dc.subjectData Analyticsen_US
dc.subjectNetwork Securityen_US
dc.titlePrivacy Preserving Network Security Data Analyticsen_US
dc.typeDissertationen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Engineeringen_US
dc.contributor.committeechairTront, Joseph G.en_US
dc.contributor.committeememberButt, Alien_US
dc.contributor.committeememberRansbottom, Jeffrey Scoten_US
dc.contributor.committeememberRaymond, David Richarden_US
dc.contributor.committeememberMidkiff, Scott F.en_US
dc.contributor.committeememberMarathe, Madhav Vishnuen_US


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