https://doi.org/10.36719/2663-4619/112/154-157
Anvar Mizanfarli
Azerbaijan Technical University
Master student
https://orcid.org/0009-0006-8028-6628
prof.anvar2013@gmail.com
Adaptive Honeypot Networks: A New Approach in Cybersecurity
Abstract
As the complexity and scale of modern cyberattacks increase, traditional security mechanisms, particularly static honeypot systems, become insufficient against new and sophisticated threats. Adaptive honeypot networks enhance cybersecurity systems through dynamic adaptation capabilities. This paper examines the fundamental principles, operational mechanisms, application areas, and advantages of adaptive honeypots. Their primary function is to analyze attacks in real-time, adjust accordingly, and adapt to evolving threat models. These technologies enable security systems to learn attacker methodologies and develop new defense strategies. They play a crucial role in securing corporate networks, cloud services, and IoT devices. Additionally, adaptive honeypots facilitate early detection of cyber threats and help implement proactive countermeasures. The integration of artificial intelligence and machine learning techniques further strengthens these technologies. In the future adaptive honeypot systems will become a key component of cybersecurity strategies, offering more flexible defenses against various attack vectors. They provide security experts with real-world attack scenarios, aiding in the development of more robust security solutions. Moreover, these systems contribute to global cyber threat monitoring and prevention, becoming increasingly significant for organizations and governmental institutions.
Keywords: adaptive honeypot, cybersecurity, threat detection, dynamic defense, artificial intelligence, machine learning, attack analysis