Averting Disaster Before It Strikes [[electronic resource] ] : How to Make Sure Your Subordinates Warn You While There is Still Time to Act / / by Dmitry Chernov, Ali Ayoub, Giovanni Sansavini, Didier Sornette |
Autore | Chernov Dmitry |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (XXII, 376 p. 69 illus., 35 illus. in color.) |
Disciplina | 658.155 |
Soggetto topico |
Financial risk management
Psychology, Industrial Management Security systems Automation Risk Management Work and Organizational Psychology Security Science and Technology |
ISBN | 3-031-30772-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Introduction -- The reason of the concealment -- Top 10 recommendations -- Results of the pilot project -- Discussion. |
Record Nr. | UNINA-9910731411603321 |
Chernov Dmitry | ||
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Cyber-physical distributed systems : modeling, reliability analysis and applications / / Huadong Mo, Giovanni Sansavini, M. Xie |
Autore | Mo Huadong |
Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
Descrizione fisica | 1 online resource (xv, 206 pages) |
Disciplina | 004.678 |
Soggetto topico |
Electronic data processing - Distributed processing - Simulation methods
Cooperating objects (Computer systems) - Simulation methods Internet of things - Simulation methods |
Soggetto genere / forma | Electronic books. |
ISBN |
1-119-68271-1
1-119-68270-3 1-119-68272-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acronyms and Abbreviations -- Chapter 1 Introduction -- 1.1 Challenges of Traditional Physical and Cyber Systems -- 1.2 Research Trends of CPSs -- 1.2.1 Stability of CPSs -- 1.2.2 Reliability of CPSs -- 1.3 Opportunities for CPS Applications -- 1.3.1 Managing Reliability and Feasibility of CPSs -- 1.3.2 Ensuring Cybersecurity of CPSs -- Chapter 2 Fundamentals of CPSs -- 2.1 Models for Exploring CPSs -- 2.1.1 Control-Block-Diagram for CPSs -- 2.1.1.1 Control Signal in CPSs -- 2.1.1.2 Degraded Actuator and Sensor -- 2.1.1.3 Time-Varying Model of CPSs -- 2.1.2 Implementation in TrueTime Simulator -- 2.1.2.1 Introduction of TrueTime Simulator -- 2.1.2.2 Architectures of CPSs in TrueTime -- 2.2 Evaluation and Verification of CPSs -- 2.2.1 CPS Performance Evaluation -- 2.2.1.1 CPS Performance Index -- 2.2.1.2 Reliability Evaluation of CPSs -- 2.2.2 CPS Model Verification -- 2.3 CPS Performance Improvement -- 2.3.1 PSO-Based Reliability Enhancement -- 2.3.2 Optimal PID-AGC -- Chapter 3 Stability Enhancement of CPSs -- 3.1 Integration of Physical and Cyber Models -- 3.1.1 Basics of WAPS -- 3.1.1.1 Physical Layer -- 3.1.1.2 Cyber Layer -- 3.1.1.3 WAPS Realized in TrueTime -- 3.1.2 An Illustrative WAPS -- 3.1.2.1 Illustrative Physical Layer -- 3.1.2.2 Illustrative Cyber Layer -- 3.1.2.3 Illustrative Integrated System -- 3.2 Settings of Stability Analysis -- 3.2.1 Settings for Delay Predictions -- 3.2.2 Settings for Illustrative WAPS -- 3.2.3 Cases for Illustrative WAPS -- 3.3 HMM-Based Stability Improvement -- 3.3.1 On-line Smith Predictor -- 3.3.1.1 Initialization of DHMM -- 3.3.1.2 Parameter Estimation of DHMM -- 3.3.1.3 Delay Prediction via DHMM -- 3.3.1.4 Smith Predictor Structure -- 3.3.2 Delay Predictions -- 3.3.2.1 Settings of DHMM -- 3.3.2.2 Prediction Comparison.
3.3.3 Performance of Smith Predictor -- 3.3.3.1 Settings of Smith Predictor -- 3.3.3.2 Analysis of Case 1 -- 3.3.3.3 Analysis of Case 2 -- 3.4 Stability Enhancement of Illustrative WAPS -- 3.4.1 Eigenvalue Analysis and Delay Impact -- 3.4.2 Sensitivity Analysis of Network Parameters -- 3.4.3 Optimal AGC -- 3.4.3.1 Optimal Controller Performance -- 3.4.3.2 Scenario 1 Analysis -- 3.4.3.3 Scenario 2 Analysis -- 3.4.3.4 Scenario 3 Analysis -- 3.4.3.5 Scenario 4 Analysis -- 3.4.3.6 Robustness of Optimal AGC -- Chapter 4 Reliability Analysis of CPSs -- 4.1 Conceptual DGSs -- 4.2 Mathematical Model of Degraded Network -- 4.2.1 Model of Transmission Delay -- 4.2.2 Model of Packet Dropout -- 4.2.3 Scenarios of Degraded Network -- 4.3 Modeling and Simulation of DGSs -- 4.3.1 DGS Model -- 4.3.1.1 Preliminary Model -- 4.3.1.2 Power Source Model -- 4.3.2 Data Interpolation -- 4.4 Reliability Estimation Via OPF -- 4.4.1 Data Prediction -- 4.4.2 MCS of DGSs -- 4.4.3 OPF of DGSs -- 4.4.4 Actual Cost and Reliability Analysis -- 4.5 OPF of DGSs Against Unreliable Network -- 4.5.1 Settings of Networked DGSs -- 4.5.2 OPF Under Different Demand Levels -- 4.5.3 OPF Under Entire Period -- Chapter 5 Maintenance of Aging CPSs -- 5.1 Data-driven Degradation Model for CPSs -- 5.1.1 Degraded Control System -- 5.1.2 Parameter Estimation via EM Algorithm -- 5.1.3 LFC Performance Criteria -- 5.2 Maintenance Model and Cost Model -- 5.2.1 PBM Model -- 5.2.2 Cost Model -- 5.3 Applications to DGSs -- 5.3.1 Output of Aging Generators -- 5.3.2 Impact of Aging on DGSs -- 5.3.2.1 Settings of Aging DGSs -- 5.3.2.2 Validations of Generator Performance Indexes -- 5.3.2.3 Quantitative Aging Impact -- 5.4 Applications to Gas Turbine Plant -- 5.4.1 Sensitivity Analysis of PBM -- 5.4.1.1 Impact of Degradation on LFC -- 5.4.1.2 Numerical Sensitivity Analysis. 5.4.1.3 Pictorial Sensitivity Analysis -- 5.4.2 Optimal Maintenance Strategy -- 5.4.3 Maintenance Models Comparison -- Chapter 6 Game Theory Based CPS Protection Plan -- 6.1 Vulnerability Model for CPSs -- 6.2 Multi-state Attack-Defence Game -- 6.2.1 Backgrounds of Game Model for CPSs -- 6.2.2 Mathematical Game Model -- 6.3 Attack Consequence and Optimal Defence -- 6.3.1 Damage Cost Model -- 6.3.2 Attack Uncertainty -- 6.3.3 Optimal Defence Plan -- 6.4 Applications to Distributed Generation Systems (DGSs) with Uncertain Cyber-attacks -- 6.4.1 Settings of Game Model -- 6.4.2 Optimal Protection with Constant Resource Allocation -- 6.4.2.1 Impact Under Constant Case -- 6.4.2.2 Optimal Constant Resource Allocation Fraction -- 6.4.3 Optimal Protection with Dynamic Resource Allocation -- 6.4.3.1 Vulnerability Model Under Dynamic Case -- 6.4.3.2 Optimal Dynamic Resource Allocation Fraction -- 6.4.3.3 Optimization Results Justification -- Chapter 7 Bayesian Based Cyberteam Deployment -- 7.1 Poisson Distribution based Cyber-attacks -- 7.1.1 Impacts of DoS Attack -- 7.1.2 Poisson Arrival Model Verification -- 7.1.3 Average Arrival Attacks -- 7.2 Cost of MNB Model -- 7.2.1 Regret Function of Worst Case -- 7.2.2 Upper Bound on Cost -- 7.3 Thompson-Hedge Algorithm -- 7.3.1 Hedge Algorithm -- 7.3.2 Details of Thompson-Hedge Algorithm -- 7.3.2.1 Separation of Target Regret -- 7.3.2.2 Upper Bound of .1 -- 7.3.2.3 Upper Bound of .2 -- 7.3.2.4 Upper Bound of Regret RTH -- 7.4 Applications to Smart Grids -- 7.4.1 Operation Cost of Smart Grids -- 7.4.2 Numerical Analysis of Cost Sequences -- 7.5 Performance of Thompson-Hedge Algorithm -- 7.5.1 Comparison Study Against R.EXP3 -- 7.5.2 Sensitivity to the Variation -- Chapter 8 Recent Advances in CPS Modeling, Stability and Reliability -- 8.1 Modeling Techniques for CPS Components -- 8.1.1 Inverse Gaussian Process. 8.1.2 Hitting Time to a Curved Boundary -- 8.1.3 Estimator Error -- 8.2 Theoretical Stability Analysis -- 8.2.1 Impacts of Uncertainties -- 8.2.2 Small Gain Theorem based Stability Criteria -- 8.2.3 Robust Stability Criteria -- 8.3 Game Model for CPSs -- References -- Index -- EULA. |
Record Nr. | UNINA-9910554832803321 |
Mo Huadong | ||
Hoboken, New Jersey : , : Wiley, , [2021] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Cyber-physical distributed systems : modeling, reliability analysis and applications / / Huadong Mo, Giovanni Sansavini, M. Xie |
Autore | Mo Huadong |
Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
Descrizione fisica | 1 online resource (xv, 206 pages) |
Disciplina | 004.678 |
Soggetto topico |
Electronic data processing - Distributed processing - Simulation methods
Cooperating objects (Computer systems) - Simulation methods Internet of things - Simulation methods |
ISBN |
1-119-68271-1
1-119-68270-3 1-119-68272-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acronyms and Abbreviations -- Chapter 1 Introduction -- 1.1 Challenges of Traditional Physical and Cyber Systems -- 1.2 Research Trends of CPSs -- 1.2.1 Stability of CPSs -- 1.2.2 Reliability of CPSs -- 1.3 Opportunities for CPS Applications -- 1.3.1 Managing Reliability and Feasibility of CPSs -- 1.3.2 Ensuring Cybersecurity of CPSs -- Chapter 2 Fundamentals of CPSs -- 2.1 Models for Exploring CPSs -- 2.1.1 Control-Block-Diagram for CPSs -- 2.1.1.1 Control Signal in CPSs -- 2.1.1.2 Degraded Actuator and Sensor -- 2.1.1.3 Time-Varying Model of CPSs -- 2.1.2 Implementation in TrueTime Simulator -- 2.1.2.1 Introduction of TrueTime Simulator -- 2.1.2.2 Architectures of CPSs in TrueTime -- 2.2 Evaluation and Verification of CPSs -- 2.2.1 CPS Performance Evaluation -- 2.2.1.1 CPS Performance Index -- 2.2.1.2 Reliability Evaluation of CPSs -- 2.2.2 CPS Model Verification -- 2.3 CPS Performance Improvement -- 2.3.1 PSO-Based Reliability Enhancement -- 2.3.2 Optimal PID-AGC -- Chapter 3 Stability Enhancement of CPSs -- 3.1 Integration of Physical and Cyber Models -- 3.1.1 Basics of WAPS -- 3.1.1.1 Physical Layer -- 3.1.1.2 Cyber Layer -- 3.1.1.3 WAPS Realized in TrueTime -- 3.1.2 An Illustrative WAPS -- 3.1.2.1 Illustrative Physical Layer -- 3.1.2.2 Illustrative Cyber Layer -- 3.1.2.3 Illustrative Integrated System -- 3.2 Settings of Stability Analysis -- 3.2.1 Settings for Delay Predictions -- 3.2.2 Settings for Illustrative WAPS -- 3.2.3 Cases for Illustrative WAPS -- 3.3 HMM-Based Stability Improvement -- 3.3.1 On-line Smith Predictor -- 3.3.1.1 Initialization of DHMM -- 3.3.1.2 Parameter Estimation of DHMM -- 3.3.1.3 Delay Prediction via DHMM -- 3.3.1.4 Smith Predictor Structure -- 3.3.2 Delay Predictions -- 3.3.2.1 Settings of DHMM -- 3.3.2.2 Prediction Comparison.
3.3.3 Performance of Smith Predictor -- 3.3.3.1 Settings of Smith Predictor -- 3.3.3.2 Analysis of Case 1 -- 3.3.3.3 Analysis of Case 2 -- 3.4 Stability Enhancement of Illustrative WAPS -- 3.4.1 Eigenvalue Analysis and Delay Impact -- 3.4.2 Sensitivity Analysis of Network Parameters -- 3.4.3 Optimal AGC -- 3.4.3.1 Optimal Controller Performance -- 3.4.3.2 Scenario 1 Analysis -- 3.4.3.3 Scenario 2 Analysis -- 3.4.3.4 Scenario 3 Analysis -- 3.4.3.5 Scenario 4 Analysis -- 3.4.3.6 Robustness of Optimal AGC -- Chapter 4 Reliability Analysis of CPSs -- 4.1 Conceptual DGSs -- 4.2 Mathematical Model of Degraded Network -- 4.2.1 Model of Transmission Delay -- 4.2.2 Model of Packet Dropout -- 4.2.3 Scenarios of Degraded Network -- 4.3 Modeling and Simulation of DGSs -- 4.3.1 DGS Model -- 4.3.1.1 Preliminary Model -- 4.3.1.2 Power Source Model -- 4.3.2 Data Interpolation -- 4.4 Reliability Estimation Via OPF -- 4.4.1 Data Prediction -- 4.4.2 MCS of DGSs -- 4.4.3 OPF of DGSs -- 4.4.4 Actual Cost and Reliability Analysis -- 4.5 OPF of DGSs Against Unreliable Network -- 4.5.1 Settings of Networked DGSs -- 4.5.2 OPF Under Different Demand Levels -- 4.5.3 OPF Under Entire Period -- Chapter 5 Maintenance of Aging CPSs -- 5.1 Data-driven Degradation Model for CPSs -- 5.1.1 Degraded Control System -- 5.1.2 Parameter Estimation via EM Algorithm -- 5.1.3 LFC Performance Criteria -- 5.2 Maintenance Model and Cost Model -- 5.2.1 PBM Model -- 5.2.2 Cost Model -- 5.3 Applications to DGSs -- 5.3.1 Output of Aging Generators -- 5.3.2 Impact of Aging on DGSs -- 5.3.2.1 Settings of Aging DGSs -- 5.3.2.2 Validations of Generator Performance Indexes -- 5.3.2.3 Quantitative Aging Impact -- 5.4 Applications to Gas Turbine Plant -- 5.4.1 Sensitivity Analysis of PBM -- 5.4.1.1 Impact of Degradation on LFC -- 5.4.1.2 Numerical Sensitivity Analysis. 5.4.1.3 Pictorial Sensitivity Analysis -- 5.4.2 Optimal Maintenance Strategy -- 5.4.3 Maintenance Models Comparison -- Chapter 6 Game Theory Based CPS Protection Plan -- 6.1 Vulnerability Model for CPSs -- 6.2 Multi-state Attack-Defence Game -- 6.2.1 Backgrounds of Game Model for CPSs -- 6.2.2 Mathematical Game Model -- 6.3 Attack Consequence and Optimal Defence -- 6.3.1 Damage Cost Model -- 6.3.2 Attack Uncertainty -- 6.3.3 Optimal Defence Plan -- 6.4 Applications to Distributed Generation Systems (DGSs) with Uncertain Cyber-attacks -- 6.4.1 Settings of Game Model -- 6.4.2 Optimal Protection with Constant Resource Allocation -- 6.4.2.1 Impact Under Constant Case -- 6.4.2.2 Optimal Constant Resource Allocation Fraction -- 6.4.3 Optimal Protection with Dynamic Resource Allocation -- 6.4.3.1 Vulnerability Model Under Dynamic Case -- 6.4.3.2 Optimal Dynamic Resource Allocation Fraction -- 6.4.3.3 Optimization Results Justification -- Chapter 7 Bayesian Based Cyberteam Deployment -- 7.1 Poisson Distribution based Cyber-attacks -- 7.1.1 Impacts of DoS Attack -- 7.1.2 Poisson Arrival Model Verification -- 7.1.3 Average Arrival Attacks -- 7.2 Cost of MNB Model -- 7.2.1 Regret Function of Worst Case -- 7.2.2 Upper Bound on Cost -- 7.3 Thompson-Hedge Algorithm -- 7.3.1 Hedge Algorithm -- 7.3.2 Details of Thompson-Hedge Algorithm -- 7.3.2.1 Separation of Target Regret -- 7.3.2.2 Upper Bound of .1 -- 7.3.2.3 Upper Bound of .2 -- 7.3.2.4 Upper Bound of Regret RTH -- 7.4 Applications to Smart Grids -- 7.4.1 Operation Cost of Smart Grids -- 7.4.2 Numerical Analysis of Cost Sequences -- 7.5 Performance of Thompson-Hedge Algorithm -- 7.5.1 Comparison Study Against R.EXP3 -- 7.5.2 Sensitivity to the Variation -- Chapter 8 Recent Advances in CPS Modeling, Stability and Reliability -- 8.1 Modeling Techniques for CPS Components -- 8.1.1 Inverse Gaussian Process. 8.1.2 Hitting Time to a Curved Boundary -- 8.1.3 Estimator Error -- 8.2 Theoretical Stability Analysis -- 8.2.1 Impacts of Uncertainties -- 8.2.2 Small Gain Theorem based Stability Criteria -- 8.2.3 Robust Stability Criteria -- 8.3 Game Model for CPSs -- References -- Index -- EULA. |
Record Nr. | UNINA-9910830372703321 |
Mo Huadong | ||
Hoboken, New Jersey : , : Wiley, , [2021] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|