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dc.contributor.advisorYu, Ning
dc.contributor.authorThurnau, Carl Jake
dc.date.accessioned2021-09-08T14:17:06Z
dc.date.available2021-09-08T14:17:06Z
dc.date.issued2020-09-16
dc.identifier.urihttp://hdl.handle.net/20.500.12648/6871
dc.description.abstractThe focus of this research article is on defenses to a theoretical threat model of malware. The malware, or GUI-Attack, aims to search the victim computer’s desktop and use image recognition to find the icons for highly used web browsers such as Google Chrome, Internet Explorer, Mozilla Firefox, and Opera, and gain access to secure data and information. We propose that adversarial examples can be used as a defensive mechanism to protect secure information from these GUI-Attacks. We hope to prove that these adversarial examples can be used to prevent malicious AI from being able to recognize the icons for popular web browsers, making an effective defensive mechanism against AI-powered GUI-Attacks.
dc.subjectMalware
dc.subjectGUI-Attack
dc.subjectWeb Browsers
dc.subjectSecure Data
dc.subjectAdversarial
dc.titleUsage of Adversarial Examples as a Defensive Mechanism in Cybersecurity
dc.typethesis
refterms.dateFOA2021-09-08T14:17:06Z
dc.description.institutionSUNY Brockport
dc.description.departmentComputing Sciences
dc.source.statuspublished
dc.description.publicationtitleSenior Honors Theses
dc.contributor.organizationState University of New York College at Brockport
dc.languate.isoen_US


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