Privacy-Enhancing Aggregation Techniques for Smart Grid Communications

• Κύριος συγγραφέας: Lu, Rongxing (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Σειρά: Wireless Networks,
• Θέματα: Computer science.; Computer communication systems.; Computer security.; Data encryption (Computer science).; Electrical engineering.; Computer Science.; Systems and Data Security.; Computer Communication Networks.; Communications Engineering, Networks.; Data Encryption.

 This book provides an overview of security and privacy issues in smart grid communications, as well as the challenges in addressing these issues. It also introduces several privacy enhancing aggregation techniques including multidimensional data aggregation, subset data aggregation, multifunctional data aggregation, data aggregation with fault tolerance, data aggregation with differential privacy, and data aggregation with integrity protection. Offering a comprehensive exploration of various privacy preserving data aggregation techniques, this book is an exceptional resource for the academics, researchers, and graduate students seeking to exploit secure data aggregation techniques in smart grid communications and Internet of Things (IoT) scenarios. 

 Introduction -- Homomorphic Public Key Encryption Techniques -- Privacy-Preserving Multidimensional Data Aggregation -- Privacy-Preserving Subset Data Aggregation -- Privacy-Preserving Multifunctional Data Aggregation -- Privacy-Preserving Data Aggregation with Fault Tolerance -- Differentially Private Data Aggregation with Fault Tolerance -- Privacy-Preserving Data Aggregation with Data Integrity and Fault Tolerance.