Thames / Schaefer Cybersecurity for Industry 4.0

Analysis for Design and Manufacturing
1. Auflage 2017
ISBN: 978-3-319-50660-9
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 273 Seiten

Reihe: Springer Series in Advanced Manufacturing

This book introduces readers to cybersecurity and its impact on the realization of the Industry 4.0 vision. It covers the technological foundations of cybersecurity within the scope of the Industry 4.0 landscape and details the existing cybersecurity threats faced by Industry 4.0, as well as state-of-the-art solutions with regard to both academic research and practical implementations. Industry 4.0 and its associated technologies, such as the Industrial Internet of Things and cloud-based design and manufacturing systems are examined, along with their disruptive innovations. Further, the book analyzes how these phenomena capitalize on the economies of scale provided by the Internet.The book offers a valuable resource for practicing engineers and decision makers in industry, as well as researchers in the design and manufacturing communities and all those interested in Industry 4.0 and cybersecurity.

Lane Thames has more than fifteen years experience in information technology, computer communications, and software engineering, all with a focus on cybersecurity. Over the past 10 years, he has conducted research at the intersection of cybersecurity, advanced information technologies, advanced manufacturing, and machine learning. His PhD dissertation was focused on distributed Internet cybersecurity, high-speed packetclassification, and autonomous cyber-attack detection with machine learning algorithms. Since 2011, he has investigated numerous foundational aspects of Industry 4.0 within the scope of Cloud-based Design and Manufacturing (CBDM) along with its associated cybersecurity needs and applications. Since 2013, he has been investigating cyber security for applications within the so-called Industrial Internet and the Industrial Internet of Things.
Dirk Schaefer has more than twenty years experience in computer-aided design, engineering, and manufacturing, both in industry and academia. Over the past fifteen years, he has conducted research on product modeling, variant design, product life-cycle management, design-with-manufacture integration, standardized product data exchange, and digital and virtual engineering. Since 2011 he has been spearheading research on Cloud-based Design and Manufacturing (CBDM) and Social Product Development (SPD), which are considered high-impact areas in the context of Industry 4.0 and cyber-physical product creation.

Autoren/Hrsg.

Thames, Lane

Schaefer, Dirk

Inhaltsverzeichnis

1;Preface;6
2;Contents;9
3;Contributors;11
4;1 Industry 4.0: An Overview of Key Benefits, Technologies, and Challenges;14
4.1;1 Introduction: Background and Motivation;14
4.2;2 Industry 4.0 and Smart Manufacturing;15
4.2.1;2.1 Industrial Internet and the Industrial Internet of Things;16
4.2.2;2.2 New 21st Century Product Development Paradigms;19
4.3;3 Cloud-Based Design and Manufacturing;22
4.4;4 Defining Cloud-Based Design and Manufacturing (CBDM);24
4.4.1;4.1 Cloud Based Design;26
4.4.2;4.2 Cloud Based Manufacturing;27
4.4.3;4.3 CBDM Services;27
4.5;5 CBDM: A First Generation Implementation;29
4.5.1;5.1 An Infrastructure for Distributed Collaborative Design and Manufacturing Inspired by the Cloud Computing Paradigm;31
4.5.2;5.2 A CBDM Workflow Example;34
4.6;6 Software Defined Cloud Manufacturing;34
4.6.1;6.1 Software-Defined Systems;36
4.6.2;6.2 A Software Defined Cloud Manufacturing Architecture;38
4.6.3;6.3 SDCM Domain Specific Configuration Language;40
4.6.4;6.4 SDCM Workflow Scenarios;41
4.7;7 Closure;44
4.8;References;45
5;2 Customized Encryption of CAD Models for Cloud-Enabled Collaborative Product Development;47
5.1;Abstract;47
5.2;1 Introduction;48
5.3;2 Related Research;49
5.3.1;2.1 Watermark of CAD Models;50
5.3.2;2.2 Access Control of CAD Models in a Network Environment;51
5.3.3;2.3 Multi-level Design Data Sharing Based on the Multi-resolution Models;52
5.3.4;2.4 Encryption of CAD Models;53
5.3.5;2.5 Summary of the Related Works;53
5.4;3 Customized Encryption of Feature-Based CAD Models;53
5.4.1;3.1 Encryption of a CAD Model;54
5.4.1.1;3.1.1 Encryption of Sketches;56
5.4.1.2;3.1.2 Encryption Algorithm of CAD Models;59
5.4.2;3.2 Encryption Based Secure Sharing of CAD Models;61
5.4.2.1;3.2.1 Key-Based Authorization Algorithm;61
5.4.2.2;3.2.2 Customized Geometric Transformation Algorithm;63
5.5;4 Case Study for Approach Validation;63
5.6;5 Conclusion and Future Works;66
5.7;Acknowledgements;67
5.8;References;67
6;3 A New Approach to Cyberphysical Security in Industry 4.0;70
6.1;Abstract;70
6.2;1 Introduction;70
6.3;2 Background;71
6.4;3 Secure Manufacturing Information Architecture;74
6.4.1;3.1 Pilot of Direct-to-Machine Security;78
6.5;4 Manufacturing Security Enforcement Device;79
6.6;5 Pilot of the Manufacturing Security Enforcement Device;80
6.7;6 Conclusion;80
6.8;Acknowledgements;82
6.9;References;82
7;4 SCADA System Forensic Analysis Within IIoT;84
7.1;1 Introduction;85
7.1.1;1.1 SCADA Progression and the Development of IIoT;86
7.2;2 Conceptual Architecture of a SCADA System;89
7.2.1;2.1 SCADA Hardware;90
7.2.2;2.2 SCADA Software;91
7.2.3;2.3 Networking;91
7.3;3 Examples of SCADA System Incidents Prior to IIoT;93
7.3.1;3.1 Trans-Siberian Pipeline Explosion;94
7.3.2;3.2 Maroochy Shire Water System;94
7.3.3;3.3 Stuxnet;94
7.3.4;3.4 Duqu;95
7.3.5;3.5 Flame;95
7.4;4 SCADA Forensics Within IIoT;96
7.4.1;4.1 Forensic Challenges;96
7.4.2;4.2 Current Data Acquisition Methods for SCADA Systems;99
7.5;5 Forensic Acquisition of SCADA Artefacts;99
7.5.1;5.1 Network Data Acquisition;99
7.5.2;5.2 Device Data Acquisition;101
7.5.3;5.3 Half-Life of Data Within a SCADA System;104
7.6;6 SCADA Forensic Process;104
7.6.1;6.1 Existing Incident Response Models;104
7.6.2;6.2 Forensic Methodology for SCADA Within IIoT;105
7.6.3;6.3 SCADA Forensic Workstation;108
7.7;7 Conclusion;109
7.8;8 List of Abbreviations;110
7.9;References;111
8;5 Big Data Security Intelligence for Healthcare Industry 4.0;113
8.1;Abstract;113
8.2;1 Introduction;114
8.2.1;1.1 Three Kinds of Integration in Industry 4.0;114
8.2.1.1;1.1.1 Horizontal Integration;114
8.2.1.2;1.1.2 Vertical Integration;114
8.2.1.3;1.1.3 End-To-End Engineering Integration;115
8.2.2;1.2 Big Data Use in Healthcare Industry;115
8.2.3;1.3 Challenges and Potential Solutions in Healthcare Industry;115
8.2.4;1.4 Open Research Issues in Healthcare Industry;117
8.3;2 Overview of the Smarter HealthCare Industry;117
8.3.1;2.1 Internet of Things and Internet of Everything;117
8.3.2;2.2 Recent Work in Smart Healthcare Industry;121
8.3.3;2.3 Security and Privacy Requirements in Smart HealthCare Industry;122
8.4;3 Industry 4.0 for Smart HealthCare Monitoring System;124
8.4.1;3.1 Meta Cloud-Redirection (MC-R) Architecture;124
8.4.1.1;3.1.1 Data Collection Phase;126
8.4.1.2;3.1.2 Data Transfer Phase;126
8.4.1.3;3.1.3 Data Processing Phase;126
8.4.1.3.1;Log File Processing;127
8.4.1.3.2;MapReduce Algorithm for Log Processing in Distributed Cloud Data Centers;127
8.4.1.3.3;Mapper Function;127
8.4.1.3.4;Reducer Function;128
8.4.1.4;3.1.4 Categorization of the Data;128
8.4.1.4.1;Critical Data;128
8.4.1.4.2;Sensitive Data;128
8.4.1.4.3;Normal Data;129
8.4.1.5;3.1.5 Big Data Storage Phase;129
8.4.1.6;3.1.6 Security Phase;129
8.4.2;3.2 Big Data Knowledge System for Industry 4.0 Systems;130
8.4.2.1;3.2.1 Data Volumes;130
8.4.2.2;3.2.2 Data Integrity and Security;130
8.5;4 Discussions;132
8.5.1;4.1 Security Issues in Various Cloud Deployment Models of Meta Cloud Data Storage Architecture;132
8.5.1.1;4.1.1 Security in Data Transfer;132
8.5.1.2;4.1.2 Security in Data Storage;132
8.5.1.3;4.1.3 Data Lineage;132
8.5.2;4.2 Merge Industry 4.0 with Other Healthcare Applications;133
8.6;5 Conclusion;135
8.7;References;135
9;6 Decentralized Cyber-Physical Systems: A Paradigm for Cloud-Based Smart Factory of Industry 4.0;137
9.1;Abstract;137
9.2;1 Introduction;138
9.3;2 Smart Factory of Industry 4.0;141
9.3.1;2.1 Industry 4.0;141
9.3.1.1;2.1.1 Background of Industry 4.0;141
9.3.1.2;2.1.2 Introduction of Industry 4.0;145
9.3.2;2.2 Smart Factory of Industry 4.0;148
9.3.2.1;2.2.1 Present Manufacturing Industry;148
9.3.2.2;2.2.2 Introduction to Smart Factories;151
9.3.2.2.1;Physical Factory;152
9.3.2.2.2;Adjoining Course;153
9.3.2.2.3;Cloud;154
9.3.2.2.4;Effect;155
9.4;3 Decentralized Cyber-Physical Systems Agents;156
9.4.1;3.1 Conceptual Model;156
9.4.1.1;3.1.1 Functions of Agents;156
9.4.1.2;3.1.2 The Biological Concept for Reference;159
9.4.1.3;3.1.3 Appearance and User Interface of Agents;160
9.4.2;3.2 Operation Mechanism;161
9.4.3;3.3 Key Technologies;163
9.5;4 A Cloud-Based Smart Manufacturing Paradigm;165
9.5.1;4.1 Implementation Approach;165
9.5.2;4.2 Business Model;169
9.5.2.1;4.2.1 Internal Integration Within the Company;169
9.5.2.2;4.2.2 External Integration Among the Companies;170
9.5.2.2.1;Horizontal Integration Along a Supply Chain;171
9.5.2.2.2;Cloud Factory;172
9.5.2.3;4.2.3 Service-Oriented Trend of Manufacturing;173
9.6;5 Application Case;175
9.6.1;5.1 Background;175
9.6.2;5.2 Application Situations;176
9.7;6 Conclusion;180
9.8;Acknowledgements;180
9.9;References;181
10;7 Applying and Assessing Cybersecurity Controls for Direct Digital Manufacturing (DDM) Systems;182
10.1;Abstract;182
10.2;1 Introduction;182
10.2.1;1.1 Power and Energy a Case Study: Consequence of not Addressing Security Before a Technology Infrastructure Is at a National Level;183
10.3;2 Defining Direct Digital Manufacturing;184
10.3.1;2.1 Installing a “New Printer”;185
10.4;3 Security Lessons from Past Industry Digitization;186
10.4.1;3.1 Telecommunication: An Organizational and Policy Approach to Security;186
10.4.2;3.2 Power and Energy: A Lesson About the False Separation of Operational Technology Versus Information Technology;187
10.5;4 Defining the DDM Cybersecurity Threats, Vulnerabilities, and Risk Management;188
10.5.1;4.1 Tenants of DDM Cybersecurity;189
10.5.2;4.2 DDM Cybersecurity Threats;189
10.5.3;4.3 DDM Cyber Vulnerabilities;190
10.5.4;4.4 DDM Risk Management Overview;191
10.5.5;4.5 DDM Cyber Risks: Theft, Disruption, and Sabotage;192
10.6;5 Walking the DDM Digital Thread;194
10.6.1;5.1 Data Storage and Transfers;195
10.6.2;5.2 Stereolithography File Attack Research;195
10.6.3;5.3 Printer Components;197
10.6.4;5.4 Engineering and Production Practices;198
10.6.5;5.5 Assessment Methodology;199
10.6.6;5.6 System Assessment;199
10.7;6 Recommendations;199
10.8;7 Conclusion;200
10.9;References;203
11;8 The Resource Usage Viewpoint of Industrial Control System Security: An Inference-Based Intrusion Detection System;204
11.1;Abstract;204
11.2;1 Introduction;205
11.3;2 Advanced Persistent Threat;207
11.4;3 Resource Usage View Point of Security;209
11.5;4 Related Work;216
11.6;5 RTOS, CPU Load, ICMP Network Traffic, and Machine Learning;219
11.7;6 Stuxnet-Type Threat Model;222
11.8;7 The PowerCyber Smartgrid Test-Bed;224
11.9;8 Experimental Evaluation;225
11.9.1;8.1 Experimental Setup;225
11.9.2;8.2 Experimental Procedure;225
11.10;9 Case Study: Discerning Between the Normal States of Intelligent Electronic Devices (IED) in Smartgrids;227
11.11;10 Results and Discussion;228
11.12;11 Summary and Future Work;230
11.13;Acknowledgements;231
11.14;References;231
12;9 Practical Security Aspects of the Internet of Things;233
12.1;Abstract;233
12.2;1 Introduction;234
12.3;2 IoT Security Threats;234
12.3.1;2.1 Top Security Issues in IoT Systems;235
12.3.2;2.2 The Architecture of IoT Systems;237
12.3.3;2.3 Security Issues in the IoT Stack;238
12.3.3.1;2.3.1 Threats at the IoT Edge;239
12.3.4;2.4 IoT Communication Technology;241
12.4;3 Technical Example: Remote Maintenance of Machine Tools;244
12.4.1;3.1 IoT Remote Maintenance Architecture;244
12.4.2;3.2 A Novel Modular IoT Unit;246
12.5;4 Summary and Conclusion;248
12.6;Acknowledgements;249
12.7;References;249
13;10 Cybersecurity for Industry 4.0 and Advanced Manufacturing Environments with Ensemble Intelligence;251
13.1;1 Cyberattack Detection: Methodologies and Algorithms;252
13.2;2 Cyberattack Detection and Response Within the Software-Defined Cloud Manufacturing Architecture;253
13.3;3 Neural Networks and Genetic Algorithms;254
13.3.1;3.1 Neural Networks;254
13.3.2;3.2 Genetic Algorithms;257
13.4;4 Cyberattack Detection with Ensembles of Computational Intelligence Systems;258
13.4.1;4.1 The NNO Classification Algorithm;259
13.5;5 Datasets and Performance Metrics for Evaluating Cyberattack Detection Systems;260
13.5.1;5.1 Datasets;261
13.5.2;5.2 Performance Metrics;262
13.5.3;5.3 NNO Ensemble Intelligence: Simulation Results;263
13.6;6 Summary;269
13.7;References;271