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CyberGAN: Generating High-Fidelity Cybersecurity Data with Generative Adversarial Networks (GANs)

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dc.contributor.author Gonik, Julia
dc.contributor.author Le, Joie
dc.contributor.author Zhang, Yuening
dc.contributor.author Viswanathan, Arun A
dc.date.accessioned 2022-02-03T22:47:59Z
dc.date.available 2022-02-03T22:47:59Z
dc.date.issued 2020-11-16
dc.identifier.citation ASCEND (AIAA) 2020, Las Vegas, Nevada, November 16-18, 2020
dc.identifier.clearanceno CL#20-4596
dc.identifier.uri http://hdl.handle.net/2014/53522
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2020
dc.title CyberGAN: Generating High-Fidelity Cybersecurity Data with Generative Adversarial Networks (GANs)
dc.type Presentation


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