ANALYSIS OF COMPUTER VIRUSES CREATED USING ARTIFICIAL INTELLIGENCE

Abstract

Artificial intelligence improves the modern world by opening up new possibilities in various fields, but at the same time, it creates new challenges, especially in the realm of cybersecurity. One of the most serious threats is the use of AI to create computer viruses that have the ability to self-learn, adapt to defense systems, and automatically change their code. This makes them significantly more difficult to detect and neutralize compared to traditional viruses. Various methods of virus creation using AI are analyzed. The first is adaptive self-learning viruses that use machine learning algorithms to analyze target behavior and adapt their attacks. There are also viruses with variable encryption, which utilize artificial neural networks to avoid detection. Generative Adversarial Networks (GAN) are also actively used to create new variants of malicious code, complicating traditional detection methods. Phishing attacks based on Natural Language Processing (NLP) are employed as well. AI-based autonomous botnets present another serious threat, as they enable large-scale attacks without human intervention. In response to these threats, countermeasures are analyzed. These include AI-based antivirus systems that can detect anomalies in program behavior, behavioral analysis that allows suspicious programs to be blocked, as well as dynamic analysis in sandboxes, which enables testing of suspicious files in an isolated environment. The use of cloud platforms for storing and analyzing threat data allows for rapid updates to defense mechanisms.