Results 11 to 14 of about 16 (14)
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2019
ÐÑÐµÐ´Ð¼ÐµÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÐагÑев загоÑовок на оÑнове Ñипа СÐС ÐиÑого и поÑиÑÑого. ÐÑоведен лиÑеÑаÑÑÑнÑй Ð¾Ð±Ð·Ð¾Ñ Ð¿Ð¾ Ñемам поÑоÑковой меÑаллÑÑгии, поÑиÑÑÑÑ Ð°Ð»ÑминиевÑÑ Ñплавов ÐÑоанализиÑован Ð½Ð°Ð³Ñ ...
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ÐÑÐµÐ´Ð¼ÐµÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÐагÑев загоÑовок на оÑнове Ñипа СÐС ÐиÑого и поÑиÑÑого. ÐÑоведен лиÑеÑаÑÑÑнÑй Ð¾Ð±Ð·Ð¾Ñ Ð¿Ð¾ Ñемам поÑоÑковой меÑаллÑÑгии, поÑиÑÑÑÑ Ð°Ð»ÑминиевÑÑ Ñплавов ÐÑоанализиÑован Ð½Ð°Ð³Ñ ...
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The topic of the graduation qualification work: «Identification of Potentially Malicious Code Segments in Android Applications Using Deep Learning». The goal of this work is to identify potentially malicious code segments in Android applications based on the analysis of the control flow graph using deep learning methods.
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The goal of the work is to improve the accuracy of detecting malicious network requests by expanding the training dataset using generative neural networks (GAN). The subject of the research is methods for expanding the training dataset. Problems solved during the study: â research into the peculiarities of creating malicious network requests, as well
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