Cyber-Risk Informatics : Engineering Evaluation with Data Science.

Intro -- TITLE PAGE -- TABLE OF CONTENTS -- ABOUT THE COVER -- PROLOGUE -- REVIEWS -- PREFACE -- ACKNOWLEDGMENTS AND DEDICATION -- ABOUT THE AUTHOR -- 1 METRICS, STATISTICAL QUALITY CONTROL, AND BASIC RELIABILITY IN CYBER-RISK -- 1.1 DETERMINISTIC AND STOCHASTIC CYBER-RISK METRICS -- 1.2 STATISTICAL RISK ANALYSIS -- 1.3 ACCEPTANCE SAMPLING IN QUALITY CONTROL -- 1.4 POISSON AND NORMAL APPROXIMATION TO BINOMIAL IN QUALITY CONTROL -- 1.5 BASIC STATISTICAL RELIABILITY CONCEPTS AND MC SIMULATORS -- 1.6 DISCUSSIONS AND CONCLUSION -- 1.7 EXERCISES -- REFERENCES -- 2 COMPLEX NETWORK RELIABILITY EVALUATION AND ESTIMATION IN CYBER-RISK -- 2.1 INTRODUCTION -- 2.2 OVERLAP TECHNIQUE TO CALCULATE COMPLEX NETWORK RELIABILITY -- 2.3 THE OVERLAP METHOD: MONTE CARLO AND DISCRETE EVENT SIMULATION -- 2.4 MULTISTATE SYSTEM RELIABILITY EVALUATION -- 2.5 WEIBULL TIME DISTRIBUTED RELIABILITY EVALUATION -- 2.6 DISCUSSIONS AND CONCLUSION -- APPENDIX 2.A OVERLAP ALGORITHM AND EXAMPLE -- 2.7 EXERCISES -- REFERENCES -- 3 STOPPING RULES FOR RELIABILITY AND SECURITY TESTS IN CYBER-RISK -- 3.1 INTRODUCTION -- 3.2 METHODS -- 3.3 EXAMPLES MERGING BOTH STOPPING RULES: LGM AND CPM -- 3.4 STOPPING RULE FOR TESTING IN THE TIME DOMAIN -- 3.5 DISCUSSIONS AND CONCLUSION -- 3.6 EXERCISES -- REFERENCES -- 4 SECURITY ASSESSMENT AND MANAGEMENT IN CYBER-RISK -- 4.1 INTRODUCTION -- 4.2 SECURITY METER (SM) MODEL DESIGN -- 4.3 VERIFICATION OF THE PROBABILISTIC SECURITY METER (SM) METHOD BY MONTE CARLO SIMULATION AND MATH-STATISTICAL TRIPLE-PRODUCT RULE -- 4.4 MODIFYING THE SM QUANTITATIVE MODEL FOR CATEGORICAL, HYBRID, AND NONDISJOINT DATA -- 4.5 MAINTENANCE PRIORITY DETERMINATION FOR 3 × 3 × 2 SM -- 4.6 PRIVACY METER (PM): HOW TO QUANTIFY PRIVACY BREACH -- 4.7 POLISH DECODING (DECOMPRESSION) ALGORITHM -- 4.8 DISCUSSIONS AND CONCLUSION -- 4.9 EXERCISES -- REFERENCES.

5 GAME-THEORETIC COMPUTING IN CYBER-RISK -- 5.1 HISTORICAL PERSPECTIVE TO GAME THEORY'S ORIGINS -- 5.2 APPLICATIONS OF GAME THEORY TO CYBER-SECURITY RISK -- 5.3 INTUITIVE BACKGROUND: CONCEPTS, DEFINITIONS, AND NOMENCLATURE -- 5.4 RANDOM SELECTION FOR NASH MIXED STRATEGY -- 5.5 ADVERSARIAL RISK ANALYSIS MODELS BY BANKS, RIOS, AND RIOS -- 5.6 AN ALTERNATIVE MODEL: SAHINOGLU'S SECURITY METER FOR NEUMANN AND NASH MIXED STRATEGY -- 5.7 OTHER INTERDISCIPLINARY APPLICATIONS OF RISK METERS -- 5.8 MIXED STRATEGY FOR RISK ASSESSMENT AND MANAGEMENT- UNIVERSITY SERVER AND SOCIAL NETWORK EXAMPLES -- 5.9 APPLICATION TO HOSPITAL HEALTHCARE SERVICE RISK -- 5.10 APPLICATION TO ENVIRONMETRICS AND ECOLOGY RISK -- 5.11 APPLICATION TO DIGITAL FORENSICS SECURITY RISK -- 5.12 APPLICATION TO BUSINESS CONTRACTING RISK -- 5.13 APPLICATION TO NATIONAL CYBERSECURITY RISK -- 5.14 APPLICATION TO AIRPORT SERVICE QUALITY RISK -- 5.15 APPLICATION TO OFFSHORE OIL-DRILLING SPILL AND SECURITY RISK -- 5.16 DISCUSSIONS AND CONCLUSION -- 5.17 EXERCISES -- REFERENCES -- 6 MODELING AND SIMULATION IN CYBER-RISK -- 6.1 INTRODUCTION AND A BRIEF HISTORY TO SIMULATION -- 6.2 GENERIC THEORY: CASE STUDIES ON GOODNESS OF FIT FOR UNIFORM NUMBERS -- 6.3 WHY CRUCIAL TO MANUFACTURING AND CYBER DEFENSE -- 6.4 A CROSS SECTION OF MODELING AND SIMULATION IN MANUFACTURING INDUSTRY -- 6.5 A REVIEW OF MODELING AND SIMULATION IN CYBER-SECURITY -- 6.6 APPLICATION OF QUEUING THEORY AND MULTICHANNEL SIMULATION TO CYBER-SECURITY -- 6.7 DISCUSSIONS AND CONCLUSION -- APPENDIX 6.A -- 6.8 EXERCISES -- REFERENCES -- 7 CLOUD COMPUTING IN CYBER-RISK -- 7.1 INTRODUCTION AND MOTIVATION -- 7.2 CLOUD COMPUTING RISK ASSESSMENT -- 7.3 MOTIVATION AND METHODOLOGY -- 7.4 VARIOUS APPLICATIONS TO CYBER SYSTEMS -- 7.5 LARGE CYBER SYSTEMS USING STATISTICAL METHODS.

7.6 REPAIR CREW AND PRODUCT RESERVE PLANNING TO MANAGE RISK COST EFFECTIVELY USING CYBERRISKSOLVER CLOUD MANAGEMENT JAVA TOOL -- 7.7 REMARKS FOR "PHYSICAL CLOUD" EMPLOYING PHYSICAL PRODUCTS (SERVERS, GENERATORS, COMMUNICATION TOWERS, ETC.) -- 7.8 APPLICATIONS TO "SOCIAL (HUMAN RESOURCES) CLOUD" -- 7.9 STOCHASTIC CLOUD SYSTEM SIMULATION -- 7.10 CLOUD RISK METER ANALYSIS -- 7.11 DISCUSSIONS AND CONCLUSION -- 7.12 EXERCISES -- REFERENCES -- 8 SOFTWARE RELIABILITY MODELING AND METRICS IN CYBER-RISK -- 8.1 INTRODUCTION, MOTIVATION, AND METHODOLOGY -- 8.2 HISTORY AND CLASSIFICATION OF SOFTWARE RELIABILITY MODELS -- 8.3 SOFTWARE RELIABILITY MODELS IN TIME DOMAIN -- 8.4 SOFTWARE RELIABILITY GROWTH MODELS -- 8.5 NUMERICAL EXAMPLES USING PEDAGOGUES -- 8.6 RECENT TRENDS IN SOFTWARE RELIABILITY -- 8.7 DISCUSSIONS AND CONCLUSION -- 8.8 EXERCISES -- REFERENCES -- 9 METRICS FOR SOFTWARE RELIABILITY FAILURE-COUNT MODELS IN CYBER-RISK -- 9.1 INTRODUCTION AND METHODOLOGY ON FAILURE-COUNT ESTIMATION IN SOFTWARE RELIABILITY -- 9.2 PREDICTIVE ACCURACY TO COMPARE FAILURE-COUNT MODELS -- 9.3 DISCUSSIONS AND CONCLUSION -- APPENDIX 9.A -- 9.4 EXERCISES -- REFERENCES -- 10 PRACTICAL HANDS-ON LAB TOPICS IN CYBER-RISK -- 10.1 SYSTEM HARDENING -- 10.2 EMAIL SECURITY -- 10.3 MS-DOS COMMANDS -- 10.4 LOGGING -- 10.5 FIREWALL -- 10.6 WIRELESS NETWORKS -- 10.7 DISCUSSIONS AND CONCLUSION -- APPENDIX 10.A -- 10.8 EXERCISES -- REFERENCES -- WHAT THE CYBER-RISK INFORMATICS TEXTBOOK AND THE AUTHOR ARE ABOUT? -- INDEX -- END USER LICENSE AGREEMENT.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.