Troubleshooting for Network Operators

Van Van Tong , Sami Souihi , Hai-Anh Tran , Abdelhamid Mellouk 지음

Wiley-ISTE 2023년 09월 12일 출간

작품소개

책소개

Nowadays, the Internet is becoming more and more complex due to an everincreasing number of network devices, various multimedia services and a prevalence of encrypted traffic. Therefore, in this context, this book presents a novel efficient multi modular troubleshooting architecture to overcome limitations related to encrypted traffic and high time complexity. This architecture contains five main modules: data collection, anomaly detection, temporary remediation, root cause analysis and definitive remediation. In data collection, there are two sub modules: parameter measurement and traffic classification. This architecture is implemented and validated in a software-defined networking (SDN) environment.

목차

Preface ix Introduction xi Chapter 1 State of the Art on Network Troubleshooting 1 1.1 Network troubleshooting 1 1.1.1 State of the art 2 1.1.2 Traditional troubleshooting architecture 9 1.2 Background on encryption protocols 10 1.2.1 QUIC 11 1.2.2 Other protocols 16 1.3 Drawbacks of troubleshooting with encrypted traffic 18 1.3.1 Network performance monitoring 18 1.3.2 Intrusion detection system 20 1.4 Conclusion 22 Chapter 2 Novel Global Troubleshooting Framework for Encrypted Traffic 25 2.1 Novel network troubleshooting architecture for encrypted traffic 25 2.2 Proof of concept of novel troubleshooting architecture in SDN 28 2.3 Data collection 32 2.3.1 Data classification 32 2.3.2 Monitoring tools 34 2.3.3 Parameter measurement 37 2.4 Troubleshooting dataset 40 2.4.1 Datasets for root cause analysis 40 2.4.2 Dataset for traffic classification 42 2.5 Conclusion 43 Chapter 3 Traffic Classification: Novel QUIC Traffic Classifier Based on Convolutional Neural Network 45 3.1 Introduction 45 3.2 Background 48 3.2.1 Convolutional network 48 3.2.2 Characteristics of QUIC-based applications 49 3.3 Traffic classification approaches 50 3.3.1 Port-based approaches 50 3.3.2 Payload-based approaches 51 3.3.3 Statistic-based approaches 51 3.3.4 DL-based approaches 52 3.4 Novel traffic classification method for QUIC traffic 53 3.4.1 Traffic collection 55 3.4.2 Flow-based features 55 3.4.3 Preprocessing 56 3.4.4 Novel traffic classification method 56 3.5 Experimental results 59 3.5.1 Dataset specification 59 3.5.2 Performance metrics 60 3.5.3 Performance analysis 61 3.6 Conclusion 65 Chapter 4 Anomaly Detection 67 4.1 Introduction 67 <

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작가정보

저자(글) Van Van Tong

저자(글) Sami Souihi

저자(글) Hai-Anh Tran

저자(글) Abdelhamid Mellouk