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Privacy in mobile and pervasive computing /

By: Langheinrich, Marc [author.].
Contributor(s): Schaub, Florian [author.].
Material type: materialTypeLabelBookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on mobile and pervasive computing: # 13.Publisher: [San Rafael, California] : Morgan & Claypool, 2019.Description: 1 PDF (xi, 127 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9781681731186.Subject(s): Mobile computing -- Security measures | Ubiquitous computing -- Security measures | mobile computing | pervasive computing | ubiquitous computing | Internet of Things | privacy | security | privacy-enhancing technology | privacy behavior | privacy engineeringDDC classification: 005.8 Online resources: Abstract with links to resource Also available in print.
Contents:
1. Introduction -- 1.1 Lecture goals and overview -- 1.2 Who should read this --
2. Understanding privacy -- 2.1 Codifying privacy -- 2.1.1 Historical roots -- 2.1.2 Privacy law and regulations -- 2.2 Motivating privacy -- 2.2.1 Privacy benefits -- 2.2.2 Limits of privacy -- 2.3 Conceptualizing privacy -- 2.3.1 Privacy types -- 2.3.2 Privacy constituents -- 2.3.3 Privacy expectations -- 2.3.4 A privacy taxonomy -- 2.4 Summary --
3. Mobile and pervasive computing -- 3.1 Mobile computing characteristics -- 3.1.1 Novel form factors-mobility and diversity -- 3.1.2 Power in your pocket-computation and communication -- 3.1.3 Data recording-sensing and context-awareness -- 3.1.4 Software ecosystems, the device as a platform -- 3.2 Pervasive and ubiquitous computing characteristics -- 3.2.1 Embeddedness-invisible computing -- 3.2.2 Implicit interaction-understanding user intent -- 3.2.3 Ubiquity, from social to societal scale -- 3.3 Summary --
4. Privacy implications of mobile and pervasive computing -- 4.1 Data shadows, the digitization of daily life -- 4.1.1 Technological development -- 4.1.2 Privacy implications -- 4.2 From atoms to bits-automated real-world data capture -- 4.2.1 Technological development -- 4.2.2 Privacy implications -- 4.3 Profiling-predicting behavior -- 4.3.1 Technological development -- 4.3.2 Privacy implications -- 4.4 Summary --
5. Supporting privacy in mobile and pervasive computing -- 5.1 Privacy-friendly by default -- 5.2 Privacy risk communication -- 5.3 Privacy management assistance -- 5.4 Context-adaptive privacy mechanisms -- 5.5 User-centric privacy controls -- 5.6 Algorithmic accountability -- 5.7 Privacy engineering -- 5.8 Summary --
6. Conclusions -- Bibliography -- Authors' biographies.
Abstract: It is easy to imagine that a future populated with an ever-increasing number of mobile and pervasive devices that record our minute goings and doings will significantly expand the amount of information that will be collected, stored, processed, and shared about us by both corporations and governments. The vast majority of this data is likely to benefit us greatly--making our lives more convenient, efficient, and safer through custom-tailored and context-aware services that anticipate what we need, where we need it, and when we need it. But beneath all this convenience, efficiency, and safety lurks the risk of losing control and awareness of what is known about us in the many different contexts of our lives. Eventually, we may find ourselves in a situation where something we said or did will be misinterpreted and held against us, even if the activities were perfectly innocuous at the time. Even more concerning, privacy implications rarely manifest as an explicit, tangible harm. Instead, most privacy harms manifest as an absence of opportunity, which may go unnoticed even though it may substantially impact our lives. In this Synthesis Lecture, we dissect and discuss the privacy implications of mobile and pervasive computing technology. For this purpose, we not only look at how mobile and pervasive computing technology affects our expectations of--and ability to enjoy--privacy, but also look at what constitutes "privacy" in the first place, and why we should care about maintaining it. We describe key characteristics of mobile and pervasive computing technology and how those characteristics lead to privacy implications. We discuss seven approaches that can help support end-user privacy in the design of mobile and pervasive computing technologies, and set forward six challenges that will need to be addressed by future research. The prime target audience of this lecture are researchers and practitioners working in mobile and pervasive computing who want to better understand and account for the nuanced privacy implications of the technologies they are creating. Those new to either mobile and pervasive computing or privacy may also benefit from reading this book to gain an overview and deeper understanding of this highly interdisciplinary and dynamic field.
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Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBKE835
Total holds: 0

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references (pages 95-125).

1. Introduction -- 1.1 Lecture goals and overview -- 1.2 Who should read this --

2. Understanding privacy -- 2.1 Codifying privacy -- 2.1.1 Historical roots -- 2.1.2 Privacy law and regulations -- 2.2 Motivating privacy -- 2.2.1 Privacy benefits -- 2.2.2 Limits of privacy -- 2.3 Conceptualizing privacy -- 2.3.1 Privacy types -- 2.3.2 Privacy constituents -- 2.3.3 Privacy expectations -- 2.3.4 A privacy taxonomy -- 2.4 Summary --

3. Mobile and pervasive computing -- 3.1 Mobile computing characteristics -- 3.1.1 Novel form factors-mobility and diversity -- 3.1.2 Power in your pocket-computation and communication -- 3.1.3 Data recording-sensing and context-awareness -- 3.1.4 Software ecosystems, the device as a platform -- 3.2 Pervasive and ubiquitous computing characteristics -- 3.2.1 Embeddedness-invisible computing -- 3.2.2 Implicit interaction-understanding user intent -- 3.2.3 Ubiquity, from social to societal scale -- 3.3 Summary --

4. Privacy implications of mobile and pervasive computing -- 4.1 Data shadows, the digitization of daily life -- 4.1.1 Technological development -- 4.1.2 Privacy implications -- 4.2 From atoms to bits-automated real-world data capture -- 4.2.1 Technological development -- 4.2.2 Privacy implications -- 4.3 Profiling-predicting behavior -- 4.3.1 Technological development -- 4.3.2 Privacy implications -- 4.4 Summary --

5. Supporting privacy in mobile and pervasive computing -- 5.1 Privacy-friendly by default -- 5.2 Privacy risk communication -- 5.3 Privacy management assistance -- 5.4 Context-adaptive privacy mechanisms -- 5.5 User-centric privacy controls -- 5.6 Algorithmic accountability -- 5.7 Privacy engineering -- 5.8 Summary --

6. Conclusions -- Bibliography -- Authors' biographies.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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It is easy to imagine that a future populated with an ever-increasing number of mobile and pervasive devices that record our minute goings and doings will significantly expand the amount of information that will be collected, stored, processed, and shared about us by both corporations and governments. The vast majority of this data is likely to benefit us greatly--making our lives more convenient, efficient, and safer through custom-tailored and context-aware services that anticipate what we need, where we need it, and when we need it. But beneath all this convenience, efficiency, and safety lurks the risk of losing control and awareness of what is known about us in the many different contexts of our lives. Eventually, we may find ourselves in a situation where something we said or did will be misinterpreted and held against us, even if the activities were perfectly innocuous at the time. Even more concerning, privacy implications rarely manifest as an explicit, tangible harm. Instead, most privacy harms manifest as an absence of opportunity, which may go unnoticed even though it may substantially impact our lives. In this Synthesis Lecture, we dissect and discuss the privacy implications of mobile and pervasive computing technology. For this purpose, we not only look at how mobile and pervasive computing technology affects our expectations of--and ability to enjoy--privacy, but also look at what constitutes "privacy" in the first place, and why we should care about maintaining it. We describe key characteristics of mobile and pervasive computing technology and how those characteristics lead to privacy implications. We discuss seven approaches that can help support end-user privacy in the design of mobile and pervasive computing technologies, and set forward six challenges that will need to be addressed by future research. The prime target audience of this lecture are researchers and practitioners working in mobile and pervasive computing who want to better understand and account for the nuanced privacy implications of the technologies they are creating. Those new to either mobile and pervasive computing or privacy may also benefit from reading this book to gain an overview and deeper understanding of this highly interdisciplinary and dynamic field.

Also available in print.

Title from PDF title page (viewed on January 3, 2019).

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