title: ÐÐ°ÑÐ¸ÑÐ° Ð¾Ñ Ð°ÑÐ°Ðº Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸ÑÑÐ°
titleType: Subtitle
title: Protection against attacks on human gender recognition systems
Creators: name: ÐÐ°ÑÐ²Ð¸ÐµÐ½ÐºÐ¾, ÐÑÐ¸Ð½Ð°
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¸
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
Ð°ÑÐ°ÐºÐ¸ Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ Ð´ÐµÑÐµÐºÑÐ¸Ð¸ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð¿Ð¾Ð»Ð°
computer vision
attacks on object detection systems
gender recognition

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ°ÑÐ¸ÑÐ° Ð¾Ñ Ð°ÑÐ°Ðº Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°Â». Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð° Ð·Ð°ÑÐ¸ÑÑ Ð¾Ñ Ð°ÑÐ°Ðº Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð°ÑÐ°ÐºÐ¸ Ð½Ð° Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°, Ð¾ÑÐ½Ð¾Ð²ÑÐ²Ð°ÑÑÐ¸ÐµÑÑ Ð½Ð° Ð´ÐµÑÐµÐºÑÐ¸Ð¸ Ð¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð»ÑÐ´ÐµÐ¹. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿Ð¾Ð² ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ Ð·Ð°Ð´Ð°Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿Ð¾ Ð¿Ð¾Ð»Ñ. ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÑÐµÐ½Ð°ÑÐ¸ÐµÐ² Ð°ÑÐ°Ðº Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°. Ð¡Ð¾Ð·Ð´Ð°Ð½Ð¸Ðµ Ð´Ð°ÑÐ°ÑÐµÑÐ° Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸. Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð° Ð·Ð°ÑÐ¸ÑÑ Ð¾Ñ Ð°ÑÐ°Ðº Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ Ð´Ð»Ñ Ð·Ð°Ð´Ð°Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿Ð¾ Ð¿Ð¾Ð»Ñ. ÐÑÐ»Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÑÐµÐ½Ð°ÑÐ¸Ð¸ Ð°ÑÐ°Ðº Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ñ Ð´ÐµÑÐµÐºÑÐ¸Ð¸ Ð¾Ð±ÑÐµÐºÑÐ¾Ð². Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°, Ð·Ð°ÑÐ¸ÑÑÐ½Ð½Ð°Ñ Ð¾Ñ Ð°ÑÐ°Ðº Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÑ Ð¿Ð°ÑÑÐµÐ¹, Ð±ÑÐ»Ð° Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð´Ð°Ð½Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸. ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¼Ð¾Ð³ÑÑ Ð±ÑÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð¾ÑÐ½Ð¾Ð²Ñ Ð´Ð»Ñ Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð·Ð°ÑÐ¸ÑÐµÐ½Ð½ÑÑ ÑÐ¸ÑÑÐµÐ¼ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿Ð¾Ð»Ð° ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°.
description: The topic of the graduate qualification work is Â«Protection against attacks on human gender recognition systemsÂ». The purpose of the study is to implement a method of protection against attacks on human gender recognition systems. The subject of the work is attacks on neural network methods of human gender identification relying on face detection and classification. The research set the following goals: Studying the principles of existing algorithms and neural networks for gender classification tasks. Research of attack scenarios on human gender recognition systems. Creating a dataset for training and testing a neural network. Designing a method for protecting against attacks on human gender-recognition systems. During the work, existing algorithms and neural networks for gender classification tasks were studied. Scenarios of attacks on object detection systems were analyzed. The work resulted in the construction of a convolutional neural network model for human gender recognition, protected from attacks of adversary patches, and demonstrated the effectiveness of the model. The results can be used as a foundation for the design of protected human gender recognition systems.