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Privacy-Preserving in Mobile Crowdsensing / by Chuan Zhang, Tong Wu, Youqi Li, Liehuang Zhu

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
大きさ	XVII, 197 p. 1 illus : online resource
著者標目	*Zhang, Chuan author Wu, Tong author Li, Youqi author Zhu, Liehuang author SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002519	Computer Scinece R0 2005-6,2022-3				9789811983153

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一般注記	Part I. Overview and Basic Concept of Mobile Crowdsensing Technology -- Chapter 1. Introduction -- Chapter 2. Overview of Mobile Crowdsensing Technology -- Part II. Privacy-Preserving Task Allocation -- Chapter 3. Privacy-Preserving Content based Task Allocation -- Chapter 4. Privacy-Preserving Location based Task Allocation -- Part III. Privacy-Preserving Truth Discovery -- Chapter 5. Privacy-Preserving Truth Discovery with Truth Transparency -- Chapter 6. Privacy-Preserving Truth Discovery with Truth Hiding -- Chapter 7. Privacy-Preserving Truth Discovery with Task Hiding -- Part IV. Summary and Future Research Directions -- Chapter 8. Summary Mobile crowdsensing is a new sensing paradigm that utilizes the intelligence of a crowd of individuals to collect data for mobile purposes by using their portable devices, such as smartphones and wearable devices. Commonly, individuals are incentivized to collect data to fulfill a crowdsensing task released by a data requester. This “sensing as a service” elaborates our knowledge of the physical world by opening up a new door of data collection and analysis. However, with the expansion of mobile crowdsensing, privacy issues urgently need to be solved. In this book, we discuss the research background and current research process of privacy protection in mobile crowdsensing. In the first chapter, the background, system model, and threat model of mobile crowdsensing are introduced. The second chapter discusses the current techniques to protect user privacy in mobile crowdsensing. Chapter three introduces the privacy-preserving content-based task allocation scheme. Chapter four further introduces the privacy-preserving location-based task scheme. Chapter five presents the scheme of privacy-preserving truth discovery with truth transparency. Chapter six proposes the scheme of privacy-preserving truth discovery with truth hiding. Chapter seven summarizes this monograph and proposes future research directions. In summary, this book introduces the following techniques in mobile crowdsensing: 1) describe a randomizable matrix-based task-matching method to protect task privacy and enable secure content-based task allocation; 2) describe a multi-clouds randomizable matrix-based task-matching method to protect location privacy and enable secure arbitrary range queries; and 3) describe privacy-preserving truth discovery methods to support efficient and secure truth discovery. These techniques are vital to the rapid development of privacy-preserving in mobile crowdsensing HTTP:URL=https://doi.org/10.1007/978-981-19-8315-3
件　名	LCSH:Data protection—Law and legislation LCSH:Computer networks—Security measures LCSH:Mobile computing LCSH:Data protection LCSH:Cryptography LCSH:Data encryption (Computer science) LCSH:Data mining FREE:Privacy FREE:Mobile and Network Security FREE:Mobile Computing FREE:Security Services FREE:Cryptology FREE:Data Mining and Knowledge Discovery
分　類	LCC:QA76.9.A25 LCC:JC596-596.2 DC23:005.8 DC23:323.448
書誌ID	EB00001907
ISBN	9789811983153