title: ÐÐ°ÑÐ¸ÑÐ° Ð¾Ñ Ð°ÑÐ°ÐºÐ¸ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ñ Ð´Ð¾Ð»Ð³Ð¾Ð¹ ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð¿Ð°Ð¼ÑÑÑÑ
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 against attack of data poisoning based on a neural network with long short-term memory
Creators: name: ÐÐ¾Ð»Ð¾Ð»Ð¾Ð±Ð¾Ð², ÐÐ¸ÐºÐ¸ÑÐ°
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¸
Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð´Ð°Ð½Ð½ÑÑ
Ð¾ÑÐ¸ÑÑÐºÐ° Ð´Ð°Ð½Ð½ÑÑ
Ð¼ÐµÑÐ¾Ð´Ñ Ð¿ÑÐ¾ÑÐ¸Ð²Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ
ÑÐ°Ð·Ð½Ð¾ÑÐ¾Ð´Ð½ÑÐµ Ð´Ð°Ð½Ð½ÑÐµ
data poisoning
data cleaning
methods for countering data poisoning
different data

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°ÐºÐ¸ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ñ Ð´Ð¾Ð»Ð³Ð¾ ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð¿Ð°Ð¼ÑÑÑÑÂ». Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð·Ð°ÑÐ¸ÑÐ° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½ÑÑ ÑÐ¸ÑÑÐµÐ¼, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¾Ñ ÑÐ³ÑÐ¾Ð·Ñ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¾Ð±ÑÑÐ°ÑÑÐµÐ³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð¾ÑÐ¸ÑÑÐºÐ¸ Ð´Ð°Ð½Ð½ÑÑ, ÐºÐ¾ÑÐ¾ÑÑÐµ Ð¼Ð¾Ð³ÑÑ Ð±ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ñ Ð¿ÑÐ¸ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ð¸ ÑÐ¸Ð¼Ð±Ð¸Ð¾ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð½Ð° ÑÑÐ°Ð¿Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1. ÐÐ½Ð°Ð»Ð¸Ð· Ð½Ð°ÑÑÐ½Ð¾-ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¾Ð¹ Ð»Ð¸ÑÐµÑÐ°ÑÑÑÑ Ñ ÑÐµÐ»ÑÑ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ. 2. ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¸ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ðµ Ð½ÐµÐ´Ð¾ÑÑÐ°ÑÐºÐ¾Ð² ÑÐ¿Ð¾ÑÐ¾Ð±Ð¾Ð² Ð¿ÑÐ¾ÑÐ¸Ð²Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð°ÑÐ°ÐºÐµ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ. 3. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐµÐ¾ÑÐµÑÐ¸ÐºÐ¾-Ð¼Ð½Ð¾Ð¶ÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÑÐµÑÐ½Ð¸Ðº Ð°ÑÐ°Ðº Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ. 4. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¾ÑÐ¸ÑÑÐºÐ¸ Ð½Ð°Ð±Ð¾ÑÐ° Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ Ñ Ð´Ð¾Ð»Ð³Ð¾Ð¹ ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð¿Ð°Ð¼ÑÑÑÑ. 5. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¼Ð°ÐºÐµÑÐ°, ÑÐµÐ°Ð»Ð¸Ð·ÑÑÑÐµÐ³Ð¾ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ Ð¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¾ÑÐ¸ÑÑÐºÐ¸ Ð½Ð°Ð±Ð¾ÑÐ° Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ. 6. ÐÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ðµ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½Ð¾Ð¹ Ð¾ÑÐµÐ½ÐºÐ¸ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¼Ð°ÐºÐµÑÐ°. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ñ Ð¼ÐµÑÐ¾Ð´Ñ Ð·Ð°ÑÐ¸ÑÑ Ð¾Ñ Ð°ÑÐ°ÐºÐ¸ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¼Ð°ÐºÐµÑ, ÑÐµÐ°Ð»Ð¸Ð·ÑÑÑÐ¸Ð¹ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ðµ Ð´Ð²ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¿Ð¾ ÑÐ¸Ð¼Ð±Ð¸Ð¾ÑÐ¸ÑÐµÑÐºÐ¾Ð¼Ñ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿Ñ Ð´Ð»Ñ Ð¿ÑÐ¾ÑÐ¸Ð²Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ð¼ Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ. 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 Ð±Ð°Ð·Ñ Ð´Ð»Ñ Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼ Ð·Ð°ÑÐ¸ÑÑ Ð¾Ñ Ð°ÑÐ°Ðº Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð¾ÑÐ¸ÑÑÐºÐ¸ Ð´Ð°Ð½Ð½ÑÑ Ð¾Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ.
description: Topic of the final qualification work: Â«Protection against infection by data infection based on a neural network with long-term short-term memoryÂ». The aim of the work is to protect information systems using machine learning methods from the threat of poisoning the training data set. The subject of the study is data cleaning methods that can be applied to ensure the symbiotic interaction of neural networks at the training stage. Tasks to be solved in the course of the study: 1. Analysis of scientific and technical literature in order to determine the signs of data poisoning. 2. Investigation and identification of shortcomings in ways to counter the attack of data poisoning. 3. Development of a set-theoretic model of data poisoning attack techniques. 4. Development of methods and algorithms for cleaning a set of poisoned data using neural networks with a long short-term memory. 5. Development of a software layout that implements the proposed methods and algorithms for cleaning a set of poisoned data. 6. Conducting an experimental evaluation of the work of the implemented software layout. In the course of the work, methods of protection against data poisoning attacks were investigated and a software layout was developed that implements the interaction of two neural networks according to the symbiotic principle to counteract the results of poisoning. The results obtained can be used as a basis for designing complex systems for protecting against data poisoning attacks and cleaning data from the results of poisoning.