: Kianoosh G. Boroojeni, M. Hadi Amini, S. S. Iyengar
: Smart Grids: Security and Privacy Issues
: Springer-Verlag
: 9783319450506
: 1
: CHF 48,30
:
: Elektronik, Elektrotechnik, Nachrichtentechnik
: English
: 120
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF
This book provides a thorough treatment of privacy and security issues for researchers in the fields of smart grids, engineering, and computer science. It presents comprehensive insight to understanding the big picture of privacy and security challenges in both physical and information aspects of smart grids. The authors utilize an advanced interdisciplinary approach to address the existing security and privacy issues and propose legitimate countermeasures for each of them in the standpoint of both computing and electrical engineering. The proposed methods are theoretically proofed by mathematical tools and illustrated by real-world examples.

Kianoosh G. Boroojeni is a PhD candidate of computer science at FIU. He received his Computer Science B.Sc in University of Tehran, Iran (2012).research interests include network algorithms, cybersecurity, and optimization algorithms. He co-authored two books entitled 'Mathematical Theories of Distributed Sensor Networks' (published by Springer) and 'Oblivious Network Routing: Algorithms and Applications' (published by MIT Press). Currently, Kianoosh is collaborating with Dr. S.S. Iyengar on some security issues in the context of cloud computing and smart grids.

M. Hadi Amini received the B.Sc. degree from the Sharif University of Technology, Tehran, Iran, in 2011, and the M.Sc. degree from Tarbiat Modares University, Tehran, in 2013, both in Electrical Engineering. He also received the M.Sc. degree in Electrical and Computer Engineering from Carnegie Mellon University in 2015. He is currently pursuing the dual-degree Ph.D. in Electrical and Computer Engineering with the Department of Electrical and Computer Engineering, Carnegie Mellon University (CMU), Pittsburgh, PA, USA and Computer Science and Technology with the Sun Yat-sen University-CMU Joint Institute of Engineering, School of Electronics and Information Technology, Guangzhou, Guangdong, China. He is also with SYSU-CMU Shunde International Joint Research Institute, Shunde, Guangdong, China. Hadi serves as reviewer for several high impact journals and international conferences and symposiums in the field of smart grid. He has published more than 40 papers in refereed journal and international conferences in the smart grid related areas. He has been awarded the 5-year scholarship from the SYSU-CMU Joint Institute of Engineering in 2014, sustainable mobility summer fellowship from Massachusetts Institute of Technology (MIT) office of sustainability in 2015, and the deans honorary award from the president of Sharif University of Technology in 2007. His current research interests include smart grids, electric vehicles, distributed optimization methods in interdependent power and transportation networks, and state estimation.

.S. Iyengar is a leading researcher in the fields of distributed sensor networks, computational robotics, and oceanographic applications, and is perhaps best known for introducing novel data structures and algorithmic techniques for large scale computations in sensor technologies and image processing applications. He is currently the Director and Ryder Professor at Florida International University's School of Computing and Information Sciences in Miami, FL. He has published more than 500 research papers and has authored or co-authored 12 textbooks and edited 10 others. Iyengar is a Member of the European Academy of Sciences, a Fellow of the Institute of Electrical and Elec ronics Engineers (IEEE), a Fellow of National Academy of Inventors (NAI) a Fellow of th Association of Comp ting Machinery (ACM), a Fellow of the American Association for the Advancement of Science(AAAS), and Fellow of the Society for Design and Process Science (SDPS). He has received the Distinguished Alumnus Award of the Indian Institute of Science. In 1998, he was awarded the IEEE Computer Society's Technical Achievement Awardand is an IEEE Golden Core Member. Professor Iyengar is an IEEE Distinguished Visitor, SIAM Distinguished Lecturer, and ACM National Lecturer. In 2006, his paper entitled, A Fast Parallel Thinning Algorithm for the Binary Image Skeletonization, was the most frequently read article in the month of January in the International Journal of High Performance Computing Applications. His innovative work called the Brooks-Iyengar algorithm along with Prof. Richard Brooks from Clemson University is applied in industries and some real-world applications.

Preface5
Features5
Intended Audience6
Acknowledgments7
Contents8
Biography11
Kianoosh G. Boroojeni11
M. Hadi Amini11
S.S. Iyengar12
1 Overview of the Security and Privacy Issues in Smart Grids13
1.1 Security Issues in Smart Grid13
1.2 Physical Network Security15
1.3 Information Network Security18
1.3.1 Detection Mechanisms19
1.3.2 Mitigation Mechanisms19
1.4 Privacy Issues in Smart Grids20
1.4.1 k-Anonymity Cloaking21
1.4.2 Location Obfuscation21
1.4.3 Location Privacy Quantification and Formalization22
1.5 Book Structure and Outlook22
References23
Part I Physical Network Security29
2 Reliability in Smart Grids30
2.1 Introduction30
2.2 Preliminaries on Reliability Quantification33
Balancing Supply and Demand33
Demand Exceeding the Supply34
Supply Exceeding the Demand34
2.3 System Adequacy Quantification34
2.4 Congestion Prevention: An Economic Dispatch Algorithm35
2.5 Summary and Conclusion36
References39
3 Error Detection of DC Power Flow Using State Estimation41
3.1 Introduction41
3.2 Preliminaries of the DC Power Flow and State Estimation43
3.2.1 Introduction to State Estimation45
3.3 Minimum-Variance Unbiased Estimator (MVUE)46
3.3.1 Measurement Error Representation in the Linear DC Power Flow Equation47
3.3.2 Linear Model47
3.3.3 Generalized Linear Model for State Estimation48
3.4 Bayesian-Based LMMSE Estimator for DC Power Flow Estimation49
3.4.1 Linear Model49
3.4.2 Bayesian Linear Model50
3.4.3 Maximum Likelihood Estimator for DC Power Flow Estimation50
3.4.4 Bayesian-Based Linear Estimator for DC Power Flow50
3.4.5 Recursive Bayesian-Based DC Power Flow Estimation Approach for