Анализ современных исследований по защите от состязательных атак в энергетических системах
Ключевые слова:
кибератаки, искусственный интеллект, машинное обучение, состязательные атаки, модель угроз, методы защиты, обзор, энергетические системы, классификацияАннотация
Системы на основе машинного обучения в настоящее время являются привлекательными мишенями для злоумышленников, поскольку нарушение работы таких систем может иметь серьезные последствия для объектов критической инфраструктуры, в частности, энергетических систем. В связи с этим количество различных типов кибератак на системы машинного обучения, которые называются состязательными атаками, постоянно растёт, и эти атаки являются предметом изучения многих исследователей. Соответственно, ежегодно появляется множество публикаций, посвящённых обзорам состязательных атак и методов защиты от них. Многие виды состязательных атак и методы защиты в этих обзорных статьях пересекаются. Однако в более поздних исследованиях содержится информация о новых типах атак и методах защиты. Цель данной статьи – проанализировать исследования, проведённые за последние шесть лет и опубликованные в высокорейтинговых журналах, с акцентом на обзорные работы. Результатом исследования является уточнённая классификация состязательных атак, характеристика наиболее распространённых атак, а также уточнённая классификация и характеристика методов защиты от этих атак. Основное внимание в анализе уделяется состязательным атакам, нацеленным на энергетические системы. В заключительной части статьи рассматриваются преимущества и недостатки различных методов противодействия состязательным атакам.
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Опубликован
2025-12-04
Как цитировать
Котенко, И. В., Саенко, И. Б., Лаута, О. С., Садовников, В. Е., Ичетовкин, Е. А., & Ли, В. (2025). Анализ современных исследований по защите от состязательных атак в энергетических системах. Информатика и автоматизация, 24(6), 1751-1809. https://doi.org/10.15622/ia.24.6.8
Раздел
Информационная безопасность
Copyright (c) Igor Kotenko, Igor Saenko, Oleg Lauta
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