Leseprobe
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Encrypted Network Traffic Analysis
Sumaiya Thaseen Ikram, Gang Li, Xiao Liu, et al.
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Springer International Publishing 
Naturwissenschaften, Medizin, Informatik, Technik / Informatik
Beschreibung
This book provides a detailed study on sources of encrypted network traffic, methods and techniques for analyzing, classifying and detecting the encrypted traffic. The authors provide research findings and objectives in the first 5 chapters, on encrypted network traffic, protocols and applications of the encrypted network traffic. The authors also analyze the challenges and issues with encrypted network traffic. It systematically introduces the analysis and classification of encrypted traffic and methods in detecting the anomalies in encrypted traffic. The effects of traditional approaches of encrypted traffic, such as deep packet inspection and flow based approaches on various encrypted traffic applications for identifying attacks is discussed as well. This book presents intelligent techniques for analyzing the encrypted network traffic and includes case studies.
The first chapter also provides fundamentals of network traffic analysis, anomalies in the network traffic, protocols for encrypted network traffic. The second chapter presents an overview of the challenges and issues with encrypted network traffic and the new threat vectors introduced by the encrypted network traffic. Chapter 3 provides details analyzing the encrypted network traffic and classification of various kinds of encrypted network traffic. Chapter 4 discusses techniques for detecting attacks against encrypted protocols and chapter 5 analyzes AI based approaches for anomaly detection.
Researchers and professionals working in the related field of Encrypted Network Traffic will purchase this book as a reference. Advanced-level students majoring in computer science will also find this book to be a valuable resource.
Kundenbewertungen
Packet Filtering, Deep Packet Inspection, Machine Learning, Network Traffic, Malware, Security, Statistical Techniques, Threat vector, Infiltration, Performance, Anomalies, Traffic Classification, Flow based Features, Parameter Tuning, Explainable AI, Adversary, Encryption, Raw Data, Deep Learning, Protocols