Umělá inteligence a počítačový červ

Abstract

The focus of this thesis is the use of artificial intelligence in the development of computer worms. The thesis describes in detail how a computer worm can exploit artificial intelligence methods to increase its efficiency and minimize the risk of detection. It explores the use of generative artificial intelligence tools for generating malicious source code as well as the use of neural networks to make decisions regarding the execution of malicious actions. In addition, the work describes the dynamic compilation of source code at runtime and the use of steganography to hide malicious code in neural networks, allowing the worm to more effectively bypass traditional security mechanisms. This thesis also describes the propagation strategies of worms through email communication, network shares, SSH protocol, and removable media, which facilitate the efficient spread of the infection. The use of different types of payloads, from encrypting and deleting data on infected machines to performing DoS attacks, is also described, demonstrating the worm's ability to cause significant disruption to the operation and functionality of target systems.