20.500.12556/DKUM-79575 Adversarna motnja razpoznave slik nevronske mreže s pomočjo evolucijskega algoritma diplomsko delo Adversarial perturbation on neural network image recognition using an evolutionary algorithm Uspešnost prepoznavanja slik z uporabo nevronskih mrež je odvisna od parametrov in filtrov, optimiziranih skozi učni proces. Tukaj najdemo razliko v načinu prepoznavanja motivov med ljudmi in stroji. Pojavi se vrzel, ki jo napadalec s pomočjo adversarnih motenj lahko izkoristi. Slike so na videz neopazno spremenjene, ljudje razlike težko zaznajo, vendar klasifikacija nevronske mreže odpove. To delo raziskuje poustvarjanje slik z evolucijskim algoritmom. Konvolucijska nevronska mreža AlexNet po spremembi ne more prepoznati predhodno jasnih motivov. Človeku prepoznavna slika se ohrani. Pari izvirnih in poustvarjenih slik so bili primerjani z uporabo vizualne ocene in statističnih metrik. Neural networks used for image recognition heavily depend on filters and parameters optimized throughout the learning process. The difference between the way people and machines see and recognize everyday objects emerge and an attacker can use it to their advantage. The images are seemingly imperceptibly altered so that people have difficulties detecting the changes, but the classification of the neural network fails. This work explores recreating images using an evolutionary algorithm. Convolutional neural network Alexnet no longer recognizes previously clear motifs. The human recognizable image is preserved. Pairs of original and recreated images were compared using visual estimation and statistical metrics. adversarna motnja evolucijski algoritmi konvolucijske nevronske mreže računalniški vid Adversarial perturbation Convolutional neural network Avolutional algorithms Machine vision true true false [R. Kukovec] Slovenski jezik Angleški jezik Diplomsko delo/naloga 2021-07-22 17:18:45 2021-08-24 07:37:33 2022-08-09 21:44:49 0000-00-00 00:00:00 2021 0 Maribor 0 Maribor XIII, 68 str. 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.932:004.8.021(043.2) 79865859 UN_Kukovec_Rok_2021.pdf UN_Kukovec_Rok_2021.pdf 1 E0869F13ECED2B2D5059AB2445338DFE ebff18317b3edd6bdc669dba37e4067b668b9da3547da52f98dd34d8f4dcf697 c9c1c05b-ef70-11eb-9cf2-00155d581298 20.500.12556/dkum/56ed871e-cbeb-4e16-a0ba-6a15cb97cb39 https://dk.um.si/Dokument.php?lang=slv&id=151440 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0