|
ИСТИНА |
Войти в систему Регистрация |
Интеллектуальная Система Тематического Исследования НАукометрических данных |
||
Attacks on Machine Learning Models Based on the PyTorch Frameworkстатья
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 10 июля 2024 г.
- Авторы: Namiot D.E., Bidzhiev T.M.
- Журнал: Automation and Remote Control
- Том: 85
- Номер: 3
- Год издания: 2024
- Издательство: Pleiades Publishing, Ltd
- Местоположение издательства: Road Town, United Kingdom
- Первая страница: 287
- Последняя страница: 296
- Номер статьи: 10.31857/S0005117924030045
- DOI: 10.31857/S0005117924030045
- Аннотация: —This research delves into the cybersecurity implications of neural network training incloud-based services. Despite their recognition for solving IT problems, the resource-intensivenature of neural network training poses challenges, leading to increased reliance on cloud services. However, this dependence introduces new cybersecurity risks. The study focuses on anovel attack method exploiting neural network weights to discreetly distribute hidden malware.It explores seven embedding methods and four trigger types for malware activation. Additionally, the paper introduces an open-source framework automating code injection into neural network weight parameters, allowing researchers to investigate and counteract this emerging attack vector.
- Добавил в систему: Намиот Дмитрий Евгеньевич