國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Privacy-preserving in edge computing

Gao, Longxiang.

Privacy-preserving in edge computing

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Privacy-preserving in edge computingby Longxiang Gao ... [et al.].
其他作者:	Gao, Longxiang.
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	xii, 113 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Edge computingSecurity measures.
電子資源:	https://doi.org/10.1007/978-981-16-2199-4
ISBN:	9789811621994$q(electronic bk.)

Privacy-preserving in edge computing
Privacy-preserving in edge computing[electronic resource] /by Longxiang Gao ... [et al.]. - Singapore :Springer Singapore :2021. - xii, 113 p. :ill., digital ;24 cm. - Wireless networks,2366-1186. - Wireless networks..

Chapter 1 An Introduction to Edge Computing -- Chapter 2 Privacy Issues in Edge Computing -- Chapter 3 Context-Aware Privacy-Preserving in Edge Computing -- Chapter 4 Location-Aware Privacy Preserving in Edge Computing -- Chapter 5 Blockchain based Decentralized Privacy Preserving in Edge Computing -- Chapter 6 Conclusion and Future Research Issues.

With the rapid development of big data, it is necessary to transfer the massive data generated by end devices to the cloud under the traditional cloud computing model. However, the delays caused by massive data transmission no longer meet the requirements of various real-time mobile services. Therefore, the emergence of edge computing has been recently developed as a new computing paradigm that can collect and process data at the edge of the network, which brings significant convenience to solving problems such as delay, bandwidth, and off-loading in the traditional cloud computing paradigm. By extending the functions of the cloud to the edge of the network, edge computing provides effective data access control, computation, processing and storage for end devices. Furthermore, edge computing optimizes the seamless connection from the cloud to devices, which is considered the foundation for realizing the interconnection of everything. However, due to the open features of edge computing, such as content awareness, real-time computing and parallel processing, the existing problems of privacy in the edge computing environment have become more prominent. The access to multiple categories and large numbers of devices in edge computing also creates new privacy issues. In this book, we discuss on the research background and current research process of privacy protection in edge computing. In the first chapter, the state-of-the-art research of edge computing are reviewed. The second chapter discusses the data privacy issue and attack models in edge computing. Three categories of privacy preserving schemes will be further introduced in the following chapters. Chapter three introduces the context-aware privacy preserving scheme. Chapter four further introduces a location-aware differential privacy preserving scheme. Chapter five presents a new blockchain based decentralized privacy preserving in edge computing. Chapter six summarize this monograph and propose future research directions. In summary, this book introduces the following techniques in edge computing: 1) describe an MDP-based privacy-preserving model to solve context-aware data privacy in the hierarchical edge computing paradigm; 2) describe a SDN based clustering methods to solve the location-aware privacy problems in edge computing; 3) describe a novel blockchain based decentralized privacy-preserving scheme in edge computing. These techniques enable the rapid development of privacy-preserving in edge computing.

ISBN: 9789811621994$q(electronic bk.)

Standard No.: 10.1007/978-981-16-2199-4doiSubjects--Topical Terms:

892182
Edge computing
--Security measures.

LC Class. No.: QA76.583

Dewey Class. No.: 004.678

Privacy-preserving in edge computing
LDR:03869nmm a2200337 a 4500 001 598426
003 DE-He213
005 20210601073533.0
006 m d
007 cr nn 008maaau
008 211025s2021 si s 0 eng d
020 $a 9789811621994$q(electronic bk.)
020 $a 9789811621987$q(paper)
024 7 $a 10.1007/978-981-16-2199-4 $2 doi
035 $a 978-981-16-2199-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.583
072 7 $a UKN $2 bicssc
072 7 $a COM075000 $2 bisacsh
072 7 $a UKN $2 thema
082 0 4 $a 004.678 $2 23
090 $a QA76.583 $b .P961 2021
245 0 0 $a Privacy-preserving in edge computing $h [electronic resource] / $c by Longxiang Gao ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a xii, 113 p. : $b ill., digital ; $c 24 cm.
490 1 $a Wireless networks, $x 2366-1186
505 0 $a Chapter 1 An Introduction to Edge Computing -- Chapter 2 Privacy Issues in Edge Computing -- Chapter 3 Context-Aware Privacy-Preserving in Edge Computing -- Chapter 4 Location-Aware Privacy Preserving in Edge Computing -- Chapter 5 Blockchain based Decentralized Privacy Preserving in Edge Computing -- Chapter 6 Conclusion and Future Research Issues.
520 $a With the rapid development of big data, it is necessary to transfer the massive data generated by end devices to the cloud under the traditional cloud computing model. However, the delays caused by massive data transmission no longer meet the requirements of various real-time mobile services. Therefore, the emergence of edge computing has been recently developed as a new computing paradigm that can collect and process data at the edge of the network, which brings significant convenience to solving problems such as delay, bandwidth, and off-loading in the traditional cloud computing paradigm. By extending the functions of the cloud to the edge of the network, edge computing provides effective data access control, computation, processing and storage for end devices. Furthermore, edge computing optimizes the seamless connection from the cloud to devices, which is considered the foundation for realizing the interconnection of everything. However, due to the open features of edge computing, such as content awareness, real-time computing and parallel processing, the existing problems of privacy in the edge computing environment have become more prominent. The access to multiple categories and large numbers of devices in edge computing also creates new privacy issues. In this book, we discuss on the research background and current research process of privacy protection in edge computing. In the first chapter, the state-of-the-art research of edge computing are reviewed. The second chapter discusses the data privacy issue and attack models in edge computing. Three categories of privacy preserving schemes will be further introduced in the following chapters. Chapter three introduces the context-aware privacy preserving scheme. Chapter four further introduces a location-aware differential privacy preserving scheme. Chapter five presents a new blockchain based decentralized privacy preserving in edge computing. Chapter six summarize this monograph and propose future research directions. In summary, this book introduces the following techniques in edge computing: 1) describe an MDP-based privacy-preserving model to solve context-aware data privacy in the hierarchical edge computing paradigm; 2) describe a SDN based clustering methods to solve the location-aware privacy problems in edge computing; 3) describe a novel blockchain based decentralized privacy-preserving scheme in edge computing. These techniques enable the rapid development of privacy-preserving in edge computing.
650 0 $a Edge computing $x Security measures. $3 892182
650 1 4 $a Computer Communication Networks. $3 218087
650 2 4 $a Privacy. $3 268519
650 2 4 $a Mobile Computing. $3 763350
650 2 4 $a Mobile and Network Security. $3 825732
650 2 4 $a Computer Applications. $3 273760
700 1 $a Gao, Longxiang. $3 724731
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Wireless networks. $3 731203
856 4 0 $u https://doi.org/10.1007/978-981-16-2199-4
950 $a Computer Science (SpringerNature-11645)