title: ÐÐµÑÐ¾Ð´ Ð·Ð°ÑÐ¸ÑÑ Ð¾Ñ ÑÐ³ÑÐ¾Ð· Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
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: The method to protect against the threat of machine learning model extraction
Creators: name: Ð¡Ð¾ÑÐ½ÐµÐ², ÐÐ°ÐºÑÐ¸Ð¼
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Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ
Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸
ÑÐ³ÑÐ¾Ð·Ð° Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸
model extraction
security threat

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description: The topic of the graduate qualification work is Â«The method to protect against the threat of machine learning model extractionÂ». The purpose of the study is developing the method for defending against security threats aimed at extracting the model of machine learning. The research set the following goals: 1. Threat analysis of machine learning model extraction and typical attack scenarios that implement them. 2. Classification of existing ways to protect against machine learning model extraction. 3. Developing a method to defend against security threats aimed at extracting model of machine learning. 4. Building a software prototype of a system that implements protection against machine learning model extraction threats and using it to evaluate the performance of the proposed method. The work resulted in a protection method combining model distillation and mechanisms using noise extraction is proposed. A software prototype of a system that implements protection against machine learning model extraction threats has been built, which experimentally established the advantage of the proposed method over traditional noise-mining mechanisms. The results can be used as a software layer to secure machine learning systems under various model extraction attacks.