Abstract: Due to rapidly evolving cybersecurity threats, advanced defence mechanisms are essential. This paper proposes an Adaptive Honeypot System with Behavioural Analysis using the K-Means algorithm to classify threats based on behaviour. By simulating vulnerabilities, the system deceives attackers, collects data, and conducts behavioural analysis. Dynamic configurations adapt to evolving attack patterns. The system efficiently detects and responds to future threats, enhancing web security. Additionally, the system employs lightweight architectures and privacy-preserving mechanisms to comply with regulations like GDPR while maintaining high performance and adaptability. To demonstrate the efficacy of the system, experimental results include statistical trends, accuracy measurements, and graphical analyses of behavioural clustering [3] [4] [7].
Keywords: Adaptive Honeypot, Behavioural Analysis, Web Security, K-Means Algorithm
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DOI:
10.17148/IJARCCE.2024.131128
