Hybrid Botnet Detection: Integrating Network and Host Analysis for Enhanced Security

Hybrid Botnet Detection: Integrating Network and Host Analysis for Enhanced Security

Nisha Costa1, Amogh Sanzgiri 2,

1Student, Information Technology, Goa College of Engineering, Goa, India

2 Assistant Professor, Information Technology, Goa College of Engineering, Goa, India

---------------------------------------------------------------------***---------------------------------------------------------------------

Abstract - Botnets pose a significant threat to network security, enabling various malicious activities such as distributed denial-of-service (DDoS) attacks, spam campaigns, and data theft. Traditional methods of botnet detection based solely on network or host analysis have limitations in effectively detecting sophisticated botnets. Hybrid botnet detection techniques, which combine both network and host analysis, have emerged as a promising approach to enhance the accuracy and efficiency of botnet detection. This survey paper aims to provide an overview of recent advancements in hybrid botnet detection techniques, highlighting their strengths, limitations, and future research directions.

Key Words: Hybrid botnet detection, network analysis, host analysis, machine learning, command and control traffic, anomaly detection, behavior analysis, real-time detection, scalability, dynamic detection, adversarial attacks.