From the three perspectives of principles, methods, and practical applications, this book introduces the botnet’s composition, behavior characteristics, and techniques for detecting botnets. It discusses the DNS failure behavior of botnets, malicious domains generated by DGA in botnets, DNS covert channels, and deep learning features. Through these perspectives, the book presents both academic and industrial perspectives on the detection principles, methods, and practical effects of botnets and briefly introduces practical applications of tracking and tracing botnets.The book also elaborates on how to apply cutting-edge technologies such as knowledge graphs, feedback learning, graph neural networks, and generative adversarial networks to botnet detection, further enhancing detection accuracy and alert capabilities.