Multi-dimensional Urban Sensing Using Crowdsensing Data, Xiang

Автор: Chuan Zhang, Tong Wu, Youqi Li, Liehuang Zhu
Название: Privacy-Preserving in Mobile Crowdsensing
ISBN: 9811983143 ISBN-13(EAN): 9789811983146
Издательство: Springer
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Цена: 22359.00 р.
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Описание: 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.

Автор: Linghe Kong; Bowen Wang; Guihai Chen
Название: When Compressive Sensing Meets Mobile Crowdsensing
ISBN: 9811377758 ISBN-13(EAN): 9789811377754
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data.Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don’t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.

Автор: Kong Linghe, Wang Bowen, Chen Guihai
Название: When Compressive Sensing Meets Mobile Crowdsensing
ISBN: 9811377782 ISBN-13(EAN): 9789811377785
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data.Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices.