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Table of Contents
Intro
Foreword
Organization
Contents
Chapter 1: Critical Threat of Critical Infrastructures: The Human Factor
1.1 Introduction
1.2 Critical Infrastructures
1.2.1 Protection of Critical Infrastructures
1.3 The Human Factor
1.3.1 Addressing the Human Factor
1.3.2 Dealing with the Human Factor
1.3.3 Boredom and Stress
1.4 Summary
References
Chapter 2: Applications of Hopkinson Bar Technique for Capability Testing of High-Energy Absorption Materials
2.1 Introduction
2.2 SHPB Test Stand and Configurations of Test Samples
2.3 Dynamic Behavior of Energy-Absorbing Building Materials
2.4 Evaluation Indexes of Energy Absorption
2.5 Conclusion
References
Chapter 3: A Method for Approximating Circular Error Probable
3.1 Introduction
3.2 Methods for Deriving CEP
3.2.1 Stochastic Approximation
3.3 Approximation CEP by SA
3.3.1 The Ratio of Standard Deviations in CEP Estimation
3.4 Numerical Analysis
3.5 Summary
References
Chapter 4: Machine Learning Aspects of Internet Firewall Data
4.1 Introduction
4.2 Modeling Network Firewall Rules by Neural Network
4.3 NN Parameter Analysis
4.4 Classification Machine Learning Algorithms with Implementation in Firewall Data
4.5 Firewall Dataset Clustering
4.6 Conclusions
Appendices
Appendix A: Clustering
K-Means Algorithm
Appendix B: Clustering
EM Algorithm
Appendix C: Clustering
DBSCAN Algorithm
References
Chapter 5: The End of Encryption?
The Era of Quantum Computers
5.1 Introduction
5.2 Machine Based Identification
5.3 Understanding Passwords
5.4 Encryption
5.5 Quantum Computers
5.6 Quantum Apocalypse
5.7 Summary
References
Chapter 6: Can Blockchain Technology Be a Solution for Safety in No-Trust Environments?
6.1 Introduction
6.2 Safety in Traditional and Modern-Age Systems
6.3 The Blockchain
6.4 Consensus Mechanisms to Be Used
6.4.1 Proof of Work (PoW)
6.4.2 Proof of Capacity (PoC)
6.4.3 Proof of Stake (PoS)
6.4.4 Proof of Importance (PoI)
6.4.5 Delegated Proof of Stake (DPoS)
6.4.6 Proof of Burn (PoB)
6.4.7 Proof of Authority (PoA)
6.4.8 Proof of Elapsed Time (PoET)
6.4.9 Summary of Potential Disadvantages of Blockchains
6.5 Summary
References
Chapter 7: A Security Assessment of AI, Related to the Financial Institutions
7.1 Introduction
7.2 A High-Level Threat Analysis
7.2.1 Threat Actors and Their Capabilities
7.2.2 AIś Known Weaknesses
7.2.3 Use and the Role of AI in Financial Institutions
7.3 AI and Cybersecurity
7.3.1 Audit Standards
7.3.2 Risk Data and Risk Scenarios
7.4 Conclusion
References
Chapter 8: Machine Learning Based Network Intrusion Detection System for Internet of Things Cybersecurity
8.1 Introduction
8.1.1 Related Work
8.1.2 Dataset
8.2 Methods
8.2.1 Feature Selection
Foreword
Organization
Contents
Chapter 1: Critical Threat of Critical Infrastructures: The Human Factor
1.1 Introduction
1.2 Critical Infrastructures
1.2.1 Protection of Critical Infrastructures
1.3 The Human Factor
1.3.1 Addressing the Human Factor
1.3.2 Dealing with the Human Factor
1.3.3 Boredom and Stress
1.4 Summary
References
Chapter 2: Applications of Hopkinson Bar Technique for Capability Testing of High-Energy Absorption Materials
2.1 Introduction
2.2 SHPB Test Stand and Configurations of Test Samples
2.3 Dynamic Behavior of Energy-Absorbing Building Materials
2.4 Evaluation Indexes of Energy Absorption
2.5 Conclusion
References
Chapter 3: A Method for Approximating Circular Error Probable
3.1 Introduction
3.2 Methods for Deriving CEP
3.2.1 Stochastic Approximation
3.3 Approximation CEP by SA
3.3.1 The Ratio of Standard Deviations in CEP Estimation
3.4 Numerical Analysis
3.5 Summary
References
Chapter 4: Machine Learning Aspects of Internet Firewall Data
4.1 Introduction
4.2 Modeling Network Firewall Rules by Neural Network
4.3 NN Parameter Analysis
4.4 Classification Machine Learning Algorithms with Implementation in Firewall Data
4.5 Firewall Dataset Clustering
4.6 Conclusions
Appendices
Appendix A: Clustering
K-Means Algorithm
Appendix B: Clustering
EM Algorithm
Appendix C: Clustering
DBSCAN Algorithm
References
Chapter 5: The End of Encryption?
The Era of Quantum Computers
5.1 Introduction
5.2 Machine Based Identification
5.3 Understanding Passwords
5.4 Encryption
5.5 Quantum Computers
5.6 Quantum Apocalypse
5.7 Summary
References
Chapter 6: Can Blockchain Technology Be a Solution for Safety in No-Trust Environments?
6.1 Introduction
6.2 Safety in Traditional and Modern-Age Systems
6.3 The Blockchain
6.4 Consensus Mechanisms to Be Used
6.4.1 Proof of Work (PoW)
6.4.2 Proof of Capacity (PoC)
6.4.3 Proof of Stake (PoS)
6.4.4 Proof of Importance (PoI)
6.4.5 Delegated Proof of Stake (DPoS)
6.4.6 Proof of Burn (PoB)
6.4.7 Proof of Authority (PoA)
6.4.8 Proof of Elapsed Time (PoET)
6.4.9 Summary of Potential Disadvantages of Blockchains
6.5 Summary
References
Chapter 7: A Security Assessment of AI, Related to the Financial Institutions
7.1 Introduction
7.2 A High-Level Threat Analysis
7.2.1 Threat Actors and Their Capabilities
7.2.2 AIś Known Weaknesses
7.2.3 Use and the Role of AI in Financial Institutions
7.3 AI and Cybersecurity
7.3.1 Audit Standards
7.3.2 Risk Data and Risk Scenarios
7.4 Conclusion
References
Chapter 8: Machine Learning Based Network Intrusion Detection System for Internet of Things Cybersecurity
8.1 Introduction
8.1.1 Related Work
8.1.2 Dataset
8.2 Methods
8.2.1 Feature Selection