Encrypted Network Traffic Analysis (eBook)

Aswani Kumar Cherukuri, Sumaiya Thaseen Ikram, Gang Li, Xiao Liu (Autoren)

eBook Download: PDF

2024
XII, 99 Seiten
Springer International Publishing (Verlag)
978-3-031-62909-9 (ISBN)

Infos

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.

Produkt-Details

• Erscheint lt. Verlag: 24.7.2024
• Reihe/Serie: SpringerBriefs in Computer Science
• Zusatzinfo: XII, 99 p. 27 illus., 14 illus. in color.
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Netzwerke
• Schlagworte: Adversary • anomalies • Deep learning • Deep Packet Inspection • Encryption • Explainable AI • Flow based Features • Infiltration • machine learning • Malware • Network traffic • Packet Filtering • Parameter tuning • Performance • protocols • raw data • security • Statistical Techniques • threat vector • traffic classification
• ISBN-10: 3-031-62909-4 / 3031629094
• ISBN-13: 978-3-031-62909-9 / 9783031629099