DEEP TRAINING IN METHODS OF PROTECTION AGAINST ATTACKS

Abstract

In recent years, machine learning algorithms, or rather deep learning algorithms, have been
widely used in many fields, including cybersecurity. However, machine learning systems are vulnerable
to attacks by attackers, and this limits the use of machine learning, especially in nonstationary
environments with hostile actions, such as the cybersecurity field, where real attackers
exist (for example, malware developers). With the rapid development of artificial intelligence (AI)
and deep learning (GO) methods, it is important to ensure the safety and reliability of the implemented
algorithms. Recently, the vulnerability of deep learning algorithms to conflicting patterns
has been widely recognized. Fabricated samples for analysis can lead to various violations of the
behavior of deep learning models, while people will consider them safe to use. The successful implementation
of enemy attacks in real physical situations and scenarios of the real physical world
once again proves their practicality. As a result, methods of adversarial attack and defense are
attracting increasing attention from the security and machine learning communities and have
become a hot topic of research in recent years not only in Russia, but also in other countries.
Sberbank, Yandex, T1 Group, Atlas Medical Center and many others are developing competitive
solutions, including on the international market. Unfortunately, in the list of the 10 largest IT
companies, the direction of Big Data, in particular, and protection against attacks is represented
only by the T1 Group company, but the market growth potential is huge. In this paper, the theoretical
foundations, algorithms and application of methods of adversarial attacks of the enemy arepresented. Then a number of research papers on protection methods are described, covering a
wide range of research in this area. This article explores and summarizes adversarial attacks and
defenses, which represent the most up-to-date research in this field and meet the latest requirements
for information security.