title: ÐÐ°ÑÐ¸ÑÐ° Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²ÑÑ ÑÐ¸ÑÑÐµÐ¼ ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ð³Ð¾ Ð·ÑÐµÐ½Ð¸Ñ Ð¾Ñ Ð±ÑÐºÐ´Ð¾Ñ-Ð°ÑÐ°Ðº
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Protection of neural network systems of computer vision from backdoor attack
Creators: name: Ð¢ÑÑÐ½Ð¾Ð²ÑÐºÐ°Ñ, ÐÐ°Ð»ÐµÑÐ¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
Ð±ÑÐºÐ´Ð¾Ñ
ÑÑÐ¾ÑÐ½ÑÐºÐ°Ñ Ð°ÑÐ°ÐºÐ°
Ð·Ð°ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ Ð´Ð°Ð½Ð½ÑÑ
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
image classification
backdoor
trojan attack
data infection
computer vision

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description: The object of research is neural network systems of computer vision. The purpose of the work is to develop a prototype of a neural network computer vision system with a mechanism to protect against backdoor attacks. Specialized software and mathematical software pycharm was used. As a result of the study, a review of computer vision systems and existing methods of attacks on them, as well as methods for combating these attacks, was carried out. The work proposed a new protection technique based on the use of hash functions and the TLS protocol to protect the data transmission channel, which has shown its effectiveness in protecting user data from spoofing. When developing a prototype of a neural network system, the formed requirements for the system were taken into account and, on their basis, the system architecture was formed. The image backdoor injection model was developed to demonstrate the operation of the developed mechanism for detecting and mitigating backdoors. The mechanism for detecting and mitigating backdoors was developed based on the analysis of changes in the accuracy of data classification when backdoors are introduced. The results of the algorithm showed the effectiveness of the proposed method of protection against backdoor attacks. Thus, the results of the work represent a novelty in the field of protecting neural network computer vision systems from backdoor attacks and can be used to improve the security of such systems.