Autors: Tsochev, G. R., Sharabov, M. Z., Aleksandar Georgiev.
Title: Using Machine Learning Reacted with Honeypot Systems for Securing Network
Keywords: cybersecurity, honeypot, machine learning, cyber attacks

Abstract: Honeypot system is available for use by popular operating systems, and there is no limit to hardware. The system provides a security solution useful for most companies that want to protect their information and feel protected from cyber-attacks. This article shows a conceptual model for securing a network. The architecture of a machine-learning model and honeypot system for protecting the network are presented.

References

    Issue

    IEEE Conference "Automatics and Informatics 2021" (ICAI'21), 2021, Bulgaria,

    Цитирания (Citation/s):
    1. Sezgin A., Ozkan G., Boyaci A., Advancements and Challenges in AI-Powered Honeypots: A Comparative Study of Detection, Engagement and Ethical Implications, 2025, Isdfs 2025 13th International Symposium on Digital Forensics and Security, issue 0, DOI 10.1109/ISDFS65363.2025.11012038 - 2025 - в издания, индексирани в Scopus

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus