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Countering Malicious Documents and Adversarial Learning

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dc.contributor.advisor Stavrou, Angelos Smutz, Charles
dc.creator Smutz, Charles 2017-01-29T01:17:28Z 2017-01-29T01:17:28Z 2016
dc.description.abstract In order to exploit the large number of vulnerabilities offered by user
dc.format.extent 169 pages
dc.language.iso en
dc.rights Copyright 2016 Charles Smutz
dc.subject Information technology en_US
dc.subject adversarial learning en_US
dc.subject content randomization en_US
dc.subject malware en_US
dc.subject mutual agreement en_US
dc.subject Random Forests en_US
dc.title Countering Malicious Documents and Adversarial Learning
dc.type Dissertation Ph.D. Information Technology George Mason University

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