REBIUN - ODA

Descripción del título

SCADA Security : Machine L...

SCADA Security : Machine Learning Concepts for Intrusion Detection and Prevention

Almalawi, Abdulmohsen

John Wiley & Sons, Incorporated 2020

Ver

Monografía

monografia Rebiun37852280 https://catalogo.rebiun.org/rebiun/record/Rebiun37852280 m o d cr ||||||||||| 201219s2020 xx o ||| 0 eng d 9781119606352 1119606357 EBLCP eng EBLCP OCLCQ REDDC OCLCO OCLCQ HF9 Almalawi, Abdulmohsen SCADA Security Machine Learning Concepts for Intrusion Detection and Prevention Newark John Wiley & Sons, Incorporated 2020 Newark Newark John Wiley & Sons, Incorporated 1 online resource (219 p.). 1 online resource (219 p.). Text txt rdacontent computer c rdamedia online resource cr rdacarrier Wiley Series on Parallel and Distributed Computing Ser Description based upon print version of record 7.4.4 Efficiency COVER -- TITLE PAGE -- COPYRIGHT PAGE -- CONTENTS -- FOREWORD -- PREFACE -- ACRONYMS -- CHAPTER 1 Introduction -- 1.1 OVERVIEW -- 1.2 EXISTING SOLUTIONS -- 1.3 SIGNIFICANT RESEARCH PROBLEMS -- 1.4 BOOK FOCUS -- 1.5 BOOK ORGANIZATION -- CHAPTER 2 Background -- 2.1 SCADA SYSTEMS -- 2.1.1 Main Components -- 2.1.2 Architecture -- 2.1.3 Protocols -- 2.2 INTRUSION DETECTION SYSTEM (IDS) -- 2.2.1 SCADA Network-Based -- 2.2.2 SCADA Application-Based -- 2.3 IDS APPROACHES -- CHAPTER 3 SCADA-Based Security Testbed -- 3.1 MOTIVATION -- 3.2 GUIDELINES TO BUILDING A SCADA SECURITY TESTBED 3.3 SCADAVT DETAILS -- 3.3.1 The Communication Infrastructure -- 3.3.2 Computer-Based SCADA Components -- 3.3.3 SCADA Protocols's Implementation -- 3.3.4 Linking Internal/External World Components -- 3.3.5 Simulation of a Controlled Environment -- 3.4 SCADAVT APPLICATION -- 3.4.1 The SCADAVT Setup -- 3.4.2 The Water Distribution System Setup -- 3.4.3 SCADA System Setup for WDS -- 3.4.4 Configuration Steps -- 3.5 ATTACK SCENARIOS -- 3.5.1 Denial of Service (DoS) Attacks -- 3.5.2 Integrity Attacks -- 3.6 CONCLUSION -- 3.7 APPENDIX FOR THIS CHAPTER -- 3.7.1 Modbus Registers Mapping CHAPTER 4 Efficient k-Nearest Neighbour Approach Based on Various-Widths Clustering -- 4.1 INTRODUCTION -- 4.2 RELATED WORK -- 4.3 THE kNNVWC APPROACH -- 4.3.1 FWC Algorithm and Its Limitations -- 4.3.2 Various-Widths Clustering -- 4.3.3 The k-NN Search -- 4.4 EXPERIMENTAL EVALUATION -- 4.4.1 Data Sets -- 4.4.2 Performance Metrics -- 4.4.3 Impact of Cluster Size -- 4.4.4 Baseline Methods -- 4.4.5 Distance Metric -- 4.4.6 Complexity Metrics -- 4.5 CONCLUSION -- CHAPTER 5 SCADA Data-Driven Anomaly Detection -- 5.1 INTRODUCTION -- 5.2 SDAD APPROACH -- 5.2.1 Observation State of SCADA Points 5.2.2 Separation of Inconsistent Observations -- 5.2.3 Extracting Proximity-Detection Rules -- 5.2.4 Inconsistency Detection -- 5.3 EXPERIMENTAL SETUP -- 5.3.1 System Setup -- 5.3.2 WDS Scenario -- 5.3.3 Attack Scenario -- 5.3.4 Data Sets -- 5.3.5 Normalization -- 5.4 RESULTS AND ANALYSIS -- 5.4.1 Accuracy Metrics -- 5.4.2 Separation Accuracy of Inconsistent Observations -- 5.4.3 Detection Accuracy -- 5.5 SDAD LIMITATIONS -- 5.6 CONCLUSION -- CHAPTER 6 A Global Anomaly Threshold to Unsupervised Detection -- 6.1 INTRODUCTION -- 6.2 RELATED WORK -- 6.3 GATUD APPROACH 6.3.1 Learning of Most-Representative Data Sets -- 6.3.2 Decision-Making Model -- 6.4 EXPERIMENTAL SETUP -- 6.4.1 Choice of Parameters -- 6.4.2 The Candidate Classifiers -- 6.5 RESULTS AND DISCUSSION -- 6.5.1 Integrating GATUD into SDAD -- 6.5.2 Integrating GATUD into the Clustering-based Method -- 6.6 CONCLUSION -- CHAPTER 7 Threshold Password-Authenticated Secret Sharing Protocolss -- 7.1 MOTIVATION -- 7.2 EXISTING SOLUTIONS -- 7.3 DEFINITION OF SECURITY -- 7.4 TPASS PROTOCOLS -- 7.4.1 Protocol-Based on Two-Phase Commitment -- 7.4.2 Protocol Based on Zero-Knowledge Proof -- 7.4.3 Correctness Supervisory control systems Automatic control- Security measures Intrusion detection systems (Computer security) Commande supervisée Commande automatique- Sécurité- Mesures Systèmes de détection d'intrusion (Sécurité informatique) Tari, Zahir Fahad, Adil Yi, Xun Print version Almalawi, Abdulmohsen. SCADA Security : Machine Learning Concepts for Intrusion Detection and Prevention Newark : John Wiley & Sons, Incorporated,c2020 9781119606031 Wiley Series on Parallel and Distributed Computing Ser

• Localizaciones: 1
• Préstamo interbibliotecario

• Exportar
  • Dublin Core
  • Google scholar
  • RIS
  • RefWorks
• Favorito
• Compartir

Información Sólo puedes introducir una dirección de email ×

Introduce un email para compartir el título

Email Pon el email de la persona con la que deseas compartir este contenido

Error .alert.alert-info

Cerrar Compartir por email

Información Haz clic en el cuadro de texto para seleccionar el contenido y copiarlo al portapapeles

Enlace permanente https://catalogo.rebiun.org/rebiun/record/Rebiun37852280

Cerrar

monografia Rebiun37852280 https://catalogo.rebiun.org/rebiun/record/Rebiun37852280 m o d cr ||||||||||| 201219s2020 xx o ||| 0 eng d 9781119606352 1119606357 EBLCP eng EBLCP OCLCQ REDDC OCLCO OCLCQ HF9 Almalawi, Abdulmohsen SCADA Security Machine Learning Concepts for Intrusion Detection and Prevention Newark John Wiley & Sons, Incorporated 2020 Newark Newark John Wiley & Sons, Incorporated 1 online resource (219 p.). 1 online resource (219 p.). Text txt rdacontent computer c rdamedia online resource cr rdacarrier Wiley Series on Parallel and Distributed Computing Ser Description based upon print version of record 7.4.4 Efficiency COVER -- TITLE PAGE -- COPYRIGHT PAGE -- CONTENTS -- FOREWORD -- PREFACE -- ACRONYMS -- CHAPTER 1 Introduction -- 1.1 OVERVIEW -- 1.2 EXISTING SOLUTIONS -- 1.3 SIGNIFICANT RESEARCH PROBLEMS -- 1.4 BOOK FOCUS -- 1.5 BOOK ORGANIZATION -- CHAPTER 2 Background -- 2.1 SCADA SYSTEMS -- 2.1.1 Main Components -- 2.1.2 Architecture -- 2.1.3 Protocols -- 2.2 INTRUSION DETECTION SYSTEM (IDS) -- 2.2.1 SCADA Network-Based -- 2.2.2 SCADA Application-Based -- 2.3 IDS APPROACHES -- CHAPTER 3 SCADA-Based Security Testbed -- 3.1 MOTIVATION -- 3.2 GUIDELINES TO BUILDING A SCADA SECURITY TESTBED 3.3 SCADAVT DETAILS -- 3.3.1 The Communication Infrastructure -- 3.3.2 Computer-Based SCADA Components -- 3.3.3 SCADA Protocols's Implementation -- 3.3.4 Linking Internal/External World Components -- 3.3.5 Simulation of a Controlled Environment -- 3.4 SCADAVT APPLICATION -- 3.4.1 The SCADAVT Setup -- 3.4.2 The Water Distribution System Setup -- 3.4.3 SCADA System Setup for WDS -- 3.4.4 Configuration Steps -- 3.5 ATTACK SCENARIOS -- 3.5.1 Denial of Service (DoS) Attacks -- 3.5.2 Integrity Attacks -- 3.6 CONCLUSION -- 3.7 APPENDIX FOR THIS CHAPTER -- 3.7.1 Modbus Registers Mapping CHAPTER 4 Efficient k-Nearest Neighbour Approach Based on Various-Widths Clustering -- 4.1 INTRODUCTION -- 4.2 RELATED WORK -- 4.3 THE kNNVWC APPROACH -- 4.3.1 FWC Algorithm and Its Limitations -- 4.3.2 Various-Widths Clustering -- 4.3.3 The k-NN Search -- 4.4 EXPERIMENTAL EVALUATION -- 4.4.1 Data Sets -- 4.4.2 Performance Metrics -- 4.4.3 Impact of Cluster Size -- 4.4.4 Baseline Methods -- 4.4.5 Distance Metric -- 4.4.6 Complexity Metrics -- 4.5 CONCLUSION -- CHAPTER 5 SCADA Data-Driven Anomaly Detection -- 5.1 INTRODUCTION -- 5.2 SDAD APPROACH -- 5.2.1 Observation State of SCADA Points 5.2.2 Separation of Inconsistent Observations -- 5.2.3 Extracting Proximity-Detection Rules -- 5.2.4 Inconsistency Detection -- 5.3 EXPERIMENTAL SETUP -- 5.3.1 System Setup -- 5.3.2 WDS Scenario -- 5.3.3 Attack Scenario -- 5.3.4 Data Sets -- 5.3.5 Normalization -- 5.4 RESULTS AND ANALYSIS -- 5.4.1 Accuracy Metrics -- 5.4.2 Separation Accuracy of Inconsistent Observations -- 5.4.3 Detection Accuracy -- 5.5 SDAD LIMITATIONS -- 5.6 CONCLUSION -- CHAPTER 6 A Global Anomaly Threshold to Unsupervised Detection -- 6.1 INTRODUCTION -- 6.2 RELATED WORK -- 6.3 GATUD APPROACH 6.3.1 Learning of Most-Representative Data Sets -- 6.3.2 Decision-Making Model -- 6.4 EXPERIMENTAL SETUP -- 6.4.1 Choice of Parameters -- 6.4.2 The Candidate Classifiers -- 6.5 RESULTS AND DISCUSSION -- 6.5.1 Integrating GATUD into SDAD -- 6.5.2 Integrating GATUD into the Clustering-based Method -- 6.6 CONCLUSION -- CHAPTER 7 Threshold Password-Authenticated Secret Sharing Protocolss -- 7.1 MOTIVATION -- 7.2 EXISTING SOLUTIONS -- 7.3 DEFINITION OF SECURITY -- 7.4 TPASS PROTOCOLS -- 7.4.1 Protocol-Based on Two-Phase Commitment -- 7.4.2 Protocol Based on Zero-Knowledge Proof -- 7.4.3 Correctness Supervisory control systems Automatic control- Security measures Intrusion detection systems (Computer security) Commande supervisée Commande automatique- Sécurité- Mesures Systèmes de détection d'intrusion (Sécurité informatique) Tari, Zahir Fahad, Adil Yi, Xun Print version Almalawi, Abdulmohsen. SCADA Security : Machine Learning Concepts for Intrusion Detection and Prevention Newark : John Wiley & Sons, Incorporated,c2020 9781119606031 Wiley Series on Parallel and Distributed Computing Ser