This SpringerBrief covers the security and privacy challenges in fog computing, and proposes a new secure and privacy-preserving mechanisms to resolve these challenges for securing fog-assisted IoT applications. Chapter 1 introduces the architecture of fog-assisted IoT applications and the security and privacy challenges in fog computing. Chapter 2 reviews several promising privacy-enhancing techniques and illustrates examples on how to leverage these techniques to enhance the privacy of users in fog computing. Specifically, the authors divide the existing privacy-enhancing techniques into three categories: identity-hidden techniques, location privacy protection and data privacy enhancing techniques. The research is of great importance since security and privacy problems faced by fog computing impede the healthy development of its enabled IoT applications.
With the advanced privacy-enhancing techniques, the authors propose three secure andprivacy-preserving protocols for fog computing applications, including smart parking navigation, mobile crowdsensing and smart grid. Chapter 3 introduces identity privacy leakage in smart parking navigation systems, and proposes a privacy-preserving smart parking navigation system to prevent identity privacy exposure and support efficient parking guidance retrieval through road-side units (fogs) with high retrieving probability and security guarantees. Chapter 4 presents the location privacy leakage, during task allocation in mobile crowdsensing, and propose a strong privacy-preserving task allocation scheme that enables location-based task allocation and reputation-based report selection without exposing knowledge about the location and reputation for participators in mobile crowdsensing. Chapter 5 introduces the data privacy leakage in smart grid, and proposes an efficient and privacy-preserving smart metering protocol to allow collectors (fogs) to achieve real-time measurement collection with privacy-enhanced data aggregation. Finally, conclusions and future research directions are given in Chapter 6.
This brief validates the significant feature extension and efficiency improvement of IoT devices without sacrificing the security and privacy of users against dishonest fog nodes. It also provides valuable insights on the security and privacy protection for fog-enabled IoT applications. Researchers and professionals who carry out research on security and privacy in wireless communication will want to purchase this SpringerBrief. Also, advanced level students, whose main research area is mobile network security will also be interested in this SpringerBrief.
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Xiaodong Lin received the PhD degree in Information Engineering from Beijing University of Posts and Telecommunications, China, and the PhD degree (with Outstanding Achievement in Graduate Studies Award) in Electrical and Computer Engineering from the University of Waterloo, Canada. He is currently working as an Associate Professor in the School of Computer Science at the University of Guelph, Canada. His research interests include wireless communications and network security, computer forensics, software security, and applied cryptography. With the increasing advance of wireless technology and the worldwide wireless network deployment, wireless networks have been on an upswing to enable ubiquitous Internet access. Making these wireless networks secure has become a major priority to keep our cyber world safe. In the past years, his research has focused on securing vehicular ad-hoc networks (VANETs), which is an emerging wireless network paradigm. He is elevated to IEEE Fellow for his contributions in secure and privacy-preserving vehicular communications. Also, He has been researching digital forensics extensively. For example, his work on automated forensic analysis of Android applications appears at DFRWS USA 2018, a top research conference in the field of digital forensics. Dr. Lin serves as an Associate Editor for many international journals. He has served or is serving as a guest editor for many special issues of IEEE, Elsevier and Springer journals and as a symposium chair or track chair for IEEE/ACM conferences. He also served on many program committees. He was Chair of Communications and Information Security Technical Committee (CISTC) (2016-2017), IEEE Communications Society (ComSoc). He is a Fellow of the IEEE. He is also a CISSP (Certified Information Systems Security Professional).
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This SpringerBrief covers the security and privacy challenges in fog computing, and proposes a new secure and privacy-preserving mechanisms to resolve these challenges for securing fog-assisted IoT applications. Chapter 1 introduces the architecture of fog-assisted IoT applications and the security and privacy challenges in fog computing. Chapter 2 reviews several promising privacy-enhancing techniques and illustrates examples on how to leverage these techniques to enhance the privacy of users in fog computing. Specifically, the authors divide the existing privacy-enhancing techniques into three categories: identity-hidden techniques, location privacy protection and data privacy enhancing techniques. The research is of great importance since security and privacy problems faced by fog computing impede the healthy development of its enabled IoT applications.With the advanced privacy-enhancing techniques, the authors propose three secure andprivacy-preserving protocols for fog computing applications, including smart parking navigation, mobile crowdsensing and smart grid. Chapter 3 introduces identity privacy leakage in smart parking navigation systems, and proposes a privacy-preserving smart parking navigation system to prevent identity privacy exposure and support efficient parking guidance retrieval through road-side units (fogs) with high retrieving probability and security guarantees. Chapter 4 presents the location privacy leakage, during task allocation in mobile crowdsensing, and propose a strong privacy-preserving task allocation scheme that enables location-based task allocation and reputation-based report selection without exposing knowledge about the location and reputation for participators in mobile crowdsensing. Chapter 5 introduces the data privacy leakage in smart grid, and proposes an efficient and privacy-preserving smart metering protocol to allow collectors (fogs) to achieve real-time measurement collection with privacy-enhanced data aggregation. Finally, conclusions and future research directions are given in Chapter 6.This brief validates the significant feature extension and efficiency improvement of IoT devices without sacrificing the security and privacy of users against dishonest fog nodes. It also provides valuable insights on the security and privacy protection for fog-enabled IoT applications. Researchers and professionals who carry out research on security and privacy in wireless communication will want to purchase this SpringerBrief. Also, advanced level students, whose main research area is mobile network security will also be interested in this SpringerBrief. Artikel-Nr. 9783030021122
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Taschenbuch. Zustand: Neu. Privacy-Enhancing Fog Computing and Its Applications | Xiaodong Lin (u. a.) | Taschenbuch | SpringerBriefs in Electrical and Computer Engineering | xii | Englisch | 2018 | Springer | EAN 9783030021122 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 114398637
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