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Smart Grids: Security and Privacy Issues

Smart Grids: Security and Privacy Issues (Paperback)

S. S. Iyengar, Kianoosh G. Boroojeni, M. Hadi Amini (지은이)
Springer
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Smart Grids: Security and Privacy Issues
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· 제목 : Smart Grids: Security and Privacy Issues (Paperback) 
· 분류 : 외국도서 > 기술공학 > 기술공학 > 텔레커뮤니케이션
· ISBN : 9783319831978
· 쪽수 : 113쪽
· 출판일 : 2018-06-28

목차

1 Overview of the Security and Privacy Issues in Smart Grids 1.1 Security Issues in Smart Grid 1.2 Physical Network Security 1.3 Information Network Security 1.4 Privacy Issues in Smart Grids 1.5 Book Structure and Outlook I Physical Network Security 2 Reliability in Smart Grids 2.1 Introduction 2.2 Preliminaries on Reliability Quantification 2.3 System Adequacy Quantification 2.4 Congestion Prevention: An Economic Dispatch Algorithm 2.4.1 9-bus Test Network 2.4.2 IEEE 30-Bus Test Network 2.5 Summary and Conclusion 3 Error Detection of DC Power Flow using State Estimation 3.1 Introduction 3.2 Preliminaries of the DC Power Flow and State Estimation 3.2.1 Introduction to State Estimation 3.3 Minimum-Variance Unbiased Estimator (MVUE) 3.3.1 Measurement Error Representation in the Linear DC Power Flow Equation 3.3.2 Linear Model 3.3.3 Generalized Linear Model for State Estimation 3.4 Bayesian-based LMMSE Estimator for DC Power Flow Estimation 3.4.1 Linear Model 3.4.2 Bayesian Linear Model 3.4.3 Maximum Likelihood Estimator for DC Power Flow Estimation 3.4.4 Bayesian-based Linear Estimator for DC Power Flow 3.4.5 Recursive Bayesian-based DC power ow Estimation Approach for DC Power Flow Estimation 3.5 Error Detection Using Sparse Vector Recovery 3.5.1 Sparse Vector Recovery 3.5.2 Proposed Sparsity-based DC Power Flow Estimation 3.5.3 Case Study and Discussion 4 Bad Data Detection 4.1 Preliminaries on Falsification Detection Algorithms 4.1.1 Related Work 4.2 Time-Series Modeling of Load Power 4.2.1 Outline of the Proposed Methodology 4.2.2 Seasonality 4.2.3 Fitting the AR and MA Models 4.2.4 Forecast Validation Using Aikaike/Bayesian Information Criteria 4.3 Case Study 4.3.1 Stabilizing the Variance 4.3.2 Fitting the Stationary Signal to a Model with Autoregressive and Moving- Average Elements 4.3.3 Model Fine-Tuning and Evaluation 4.4 Summary and Conclusion II Information Network Security 5 Cloud Network Data Security 5.1 Introduction 5.2 Data Security Protection in Cloud-connected Smart Grids 5.2.1 Simulation Scheme 5.2.2 Simulation Results 5.3 Summary and Outlook III Privacy Preservation 6 End-User Data Privacy 6.1 Introduction 6.2 Preliminaries to Privacy Preservation Methods 6.2.1 k-Anonymity Cloaking 6.2.2 Location Obfuscation 6.2.3 Preliminary Definitions 6.3 Privacy Preservation: Location Obfuscation Methods 6.4 Summary and Conclusion 7 Mobile User Data Privacy 7.1 Introduction 7.2 Preliminaries on Mobile Nodes Trajectory Privacy 7.3 Privacy Preservation Quantification: Probabilistic Model 7.4 A Vernoi-based Location Obfuscation Method 7.4.1 A Stochastic Model of the Node Movement 7.4.2 Proposed Scheme for A Mobile Node 7.4.3 Computing the Instantaneous Privacy Level 7.4.4 Concealing the Movement Path 7.5 Summary and Conclusion

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