LEADER 04933nam 22007575 450 001 9910683350103321 005 20251009075044.0 010 $a9789811983153 010 $a9811983151 024 7 $a10.1007/978-981-19-8315-3 035 $a(MiAaPQ)EBC7219548 035 $a(Au-PeEL)EBL7219548 035 $a(OCoLC)1374034949 035 $a(DE-He213)978-981-19-8315-3 035 $a(PPN)269098992 035 $a(CKB)26313263200041 035 $a(EXLCZ)9926313263200041 100 $a20230324d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPrivacy-Preserving in Mobile Crowdsensing /$fby Chuan Zhang, Tong Wu, Youqi Li, Liehuang Zhu 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (205 pages) 311 08$aPrint version: Zhang, Chuan Privacy-Preserving in Mobile Crowdsensing Singapore : Springer,c2023 9789811983146 320 $aIncludes bibliographical references. 327 $aPart 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. 330 $aMobile 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. 606 $aData protection$xLaw and legislation 606 $aComputer networks$xSecurity measures 606 $aMobile computing 606 $aData protection 606 $aCryptography 606 $aData encryption (Computer science) 606 $aData mining 606 $aPrivacy 606 $aMobile and Network Security 606 $aMobile Computing 606 $aSecurity Services 606 $aCryptology 606 $aData Mining and Knowledge Discovery 615 0$aData protection$xLaw and legislation. 615 0$aComputer networks$xSecurity measures. 615 0$aMobile computing. 615 0$aData protection. 615 0$aCryptography. 615 0$aData encryption (Computer science) 615 0$aData mining. 615 14$aPrivacy. 615 24$aMobile and Network Security. 615 24$aMobile Computing. 615 24$aSecurity Services. 615 24$aCryptology. 615 24$aData Mining and Knowledge Discovery. 676 $a681.2 700 $aZhang$b Chu'an$01349075 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910683350103321 996 $aPrivacy-preserving in mobile crowdsensing$93417197 997 $aUNINA