Automated Test Case Generator for Phishing Prevention Using Generative Grammars and Discriminative Methods

Simple item page
dc.contributor.advisorMcCoy, Damon
dc.contributor.authorPalka, Sean
dc.creatorPalka, Sean
dc.date.accessioned2016-04-19T19:29:44Z
dc.date.available2016-04-19T19:29:44Z
dc.date.issued2015
dc.description.abstractThis research details a methodology designed for creating content in support of various phishing prevention tasks including live exercises and detection algorithm research. Our system uses probabilistic context-free grammars (PCFG) and variable interpolation as part of a multi-pass method to create diverse and consistent phishing email content on a scale not achieved in previous research. This system, which we have named PhishGen, is capable of generating a large amount of unique content that can be used in live exercises, or alternatively used to build training datasets for phishing detection methods and filter settings. PhishGen is a web-based application that implements our underlying methodology to provide a user-interface for building and modifying PCFG rules and weights. The system is released as an open-source tool in order to allow access to other researchers. PhishGen has already been used in support of live commercial phishing exercises and is in the process of being utilized for content development for commercial frameworks.
dc.format.extent177 pages
dc.identifier.urihttps://hdl.handle.net/1920/10198
dc.language.isoen
dc.rightsCopyright 2015 Sean Palka
dc.subjectInformation technology
dc.subjectCyber Security
dc.subjectGenerative Grammars
dc.subjectNatural Language Processing
dc.subjectPhishing
dc.titleAutomated Test Case Generator for Phishing Prevention Using Generative Grammars and Discriminative Methods
dc.typeDissertation
thesis.degree.disciplineInformation Technology
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Palka_gmu_0883E_11041.pdf
Size:
2.3 MB
Format:
Adobe Portable Document Format
Download

Collections

College of Engineering and Computing