Privacy Preserving In Mobile Crowdsensing

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Privacy Preserving In Mobile Crowdsensing

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Author : Chuan Zhang
language : en
Publisher: Springer Nature
Release Date : 2023-03-24

Privacy Preserving In Mobile Crowdsensing written by Chuan Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-24 with Computers categories.

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.

Incentive Mechanism For Mobile Crowdsensing

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Author : Youqi Li
language : en
Publisher: Springer Nature
Release Date : 2024-01-03

Incentive Mechanism For Mobile Crowdsensing written by Youqi Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-03 with Computers categories.

Mobile crowdsensing (MCS) is emerging as a novel sensing paradigm in the Internet of Things (IoTs) due to the proliferation of smart devices (e.g., smartphones, wearable devices) in people’s daily lives. These ubiquitous devices provide an opportunity to harness the wisdom of crowds by recruiting mobile users to collectively perform sensing tasks, which largely collect data about a wide range of human activities and the surrounding environment. However, users suffer from resource consumption such as battery, processing power, and storage, which discourages users’ participation. To ensure the participation rate, it is necessary to employ an incentive mechanism to compensate users’ costs such that users are willing to take part in crowdsensing. This book sheds light on the design of incentive mechanisms for MCS in the context of game theory. Particularly, this book presents several game-theoretic models for MCS in different scenarios. In Chapter 1, the authors present an overview of MCS and state the significance of incentive mechanism for MCS. Then, in Chapter 2, 3, 4, and 5, the authors propose a long-term incentive mechanism, a fair incentive mechanism, a collaborative incentive mechanism, and a coopetition-aware incentive mechanism for MCS, respectively. Finally, Chapter 6 summarizes this book and point out the future directions. This book is of particular interest to the readers and researchers in the field of IoT research, especially in the interdisciplinary field of network economics and IoT.

Privacy And Security For Mobile Crowdsourcing

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Author : Shabnam Sodagari
language : en
Publisher: CRC Press
Release Date : 2023-12-21

Privacy And Security For Mobile Crowdsourcing written by Shabnam Sodagari and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-21 with Technology & Engineering categories.

This concise guide to mobile crowdsourcing and crowdsensing vulnerabilities and countermeasures walks readers through a series of examples, discussions, tables, initiative figures, and diagrams to present to them security and privacy foundations and applications. Discussed approaches help build intuition to apply these concepts to a broad range of system security domains toward dimensioning of next generations of mobiles crowdsensing applications. This book offers vigorous techniques as well as new insights for both beginners and seasoned professionals. It reflects on recent advances and research achievements. Technical topics discussed in the book include but are not limited to: Risks affecting crowdsensing platforms Spatio-temporal privacy of crowdsourced applications Differential privacy for data mining crowdsourcing Blockchain-based crowdsourcing Secure wireless mobile crowdsensing. This book is accessible to readers in mobile computer/communication industries as well as academic staff and students in computer science, electrical engineering, telecommunication systems, business information systems, and crowdsourced mobile app developers.

Mobile Crowdsensing

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Author : Cristian Borcea
language : en
Publisher: CRC Press
Release Date : 2016-12-01

Mobile Crowdsensing written by Cristian Borcea and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-01 with Computers categories.

Mobile crowdsensing is a technology that allows large scale, cost-effective sensing of the physical world. In mobile crowdsensing, mobile personal devices such as smart phones or smart watches come equipped with a variety of sensors that can be leveraged to collect data related to environment, transportation, healthcare, safety and so on. This book presents the first extensive coverage of mobile crowdsensing, with examples and insights drawn from the authors’ extensive research on this topic as well as from the research and development of a growing community of researchers and practitioners working in this emerging field. Throughout the text, the authors provide the reader with various examples of crowdsensing applications and the building blocks to creating the necessary infrastructure, explore the related concepts of mobile sensing and crowdsourcing, and examine security and privacy issues introduced by mobile crowdsensing platforms. Provides a comprehensive description of mobile crowdsensing, a one-stop shop for all relevant issues pertaining to mobile crowdsensing, including motivation, applications, design and implementation, incentive mechanisms, and reliability and privacy. Describes the design and implementations of mobile crowdsensing platforms of great interest for the readers working in research and industry to quickly implement and test their systems. Identifies potential issues in building such mobile crowdsensing applications to ensure their usability in real life and presents future directions in mobile crowdsensing by emphasizing the open problems that have to be addressed.

Privacy Enhancing Fog Computing And Its Applications

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Author : Xiaodong Lin
language : en
Publisher: Springer
Release Date : 2018-11-12

Privacy Enhancing Fog Computing And Its Applications written by Xiaodong Lin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-12 with Computers categories.

This SpringerBrief covers the security and privacy challenges in fog computing, and proposes a new secure and privacy-preserving mechanisms to resolve these challenges for securing fog-assisted IoT applications. Chapter 1 introduces the architecture of fog-assisted IoT applications and the security and privacy challenges in fog computing. Chapter 2 reviews several promising privacy-enhancing techniques and illustrates examples on how to leverage these techniques to enhance the privacy of users in fog computing. Specifically, the authors divide the existing privacy-enhancing techniques into three categories: identity-hidden techniques, location privacy protection and data privacy enhancing techniques. The research is of great importance since security and privacy problems faced by fog computing impede the healthy development of its enabled IoT applications. With the advanced privacy-enhancing techniques, the authors propose three secure andprivacy-preserving protocols for fog computing applications, including smart parking navigation, mobile crowdsensing and smart grid. Chapter 3 introduces identity privacy leakage in smart parking navigation systems, and proposes a privacy-preserving smart parking navigation system to prevent identity privacy exposure and support efficient parking guidance retrieval through road-side units (fogs) with high retrieving probability and security guarantees. Chapter 4 presents the location privacy leakage, during task allocation in mobile crowdsensing, and propose a strong privacy-preserving task allocation scheme that enables location-based task allocation and reputation-based report selection without exposing knowledge about the location and reputation for participators in mobile crowdsensing. Chapter 5 introduces the data privacy leakage in smart grid, and proposes an efficient and privacy-preserving smart metering protocol to allow collectors (fogs) to achieve real-time measurement collection with privacy-enhanced data aggregation. Finally, conclusions and future research directions are given in Chapter 6. This brief validates the significant feature extension and efficiency improvement of IoT devices without sacrificing the security and privacy of users against dishonest fog nodes. It also provides valuable insights on the security and privacy protection for fog-enabled IoT applications. Researchers and professionals who carry out research on security and privacy in wireless communication will want to purchase this SpringerBrief. Also, advanced level students, whose main research area is mobile network security will also be interested in this SpringerBrief.

Security And Privacy Preservation In Mobile Crowdsensing

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Author : Jianbing Ni
language : en
Publisher:
Release Date : 2018

Security And Privacy Preservation In Mobile Crowdsensing written by Jianbing Ni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computer security categories.

Moobile crowdsensing (MCS) is a compelling paradigm that enables a crowd of individuals to cooperatively collect and share data to measure phenomena or record events of common interest using their mobile devices. Pairing with inherent mobility and intelligence, mobile users can collect, produce and upload large amounts of data to service providers based on crowdsensing tasks released by customers, ranging from general information, such as temperature, air quality and traffic condition, to more specialized data, such as recommended places, health condition and voting intentions. Compared with traditional sensor networks, MCS can support large-scale sensing applications, improve sensing data trustworthiness and reduce the cost on deploying expensive hardware or software to acquire high-quality data. Despite the appealing benefits, however, MCS is also confronted with a variety of security and privacy threats, which would impede its rapid development. Due to their own incentives and vulnerabilities of service providers, data security and user privacy are being put at risk. The corruption of sensing reports may directly affect crowdsensing results, and thereby mislead customers to make irrational decisions. Moreover, the content of crowdsensing tasks may expose the intention of customers, and the sensing reports might inadvertently reveal sensitive information about mobile users. Data encryption and anonymization techniques can provide straightforward solutions for data security and user privacy, but there are several issues, which are of significantly importance to make MCS practical. First of all, to enhance data trustworthiness, service providers need to recruit mobile users based on their personal information, such as preferences, mobility pattern and reputation, resulting in the privacy exposure to service providers. Secondly, it is inevitable to have replicate data in crowdsensing reports, which may possess large communication bandwidth, but traditional data encryption makes replicate data detection and deletion challenging. Thirdly, crowdsensed data analysis is essential to generate crowdsensing reports in MCS, but the correctness of crowdsensing results in the absence of malicious mobile users and service providers become a huge concern for customers. Finally yet importantly, even if user privacy is preserved during task allocation and data collection, it may still be exposed during reward distribution. It further discourage mobile users from task participation. In this thesis, we explore the approaches to resolve these challenges in MCS. Based on the architecture of MCS, we conduct our research with the focus on security and privacy protection without sacrificing data quality and users' enthusiasm. Specifically, the main contributions are, i) to enable privacy preservation and task allocation, we propose SPOON, a strong privacy-preserving mobile crowdsensing scheme supporting accurate task allocation. In SPOON, the service provider recruits mobile users based on their locations, and selects proper sensing reports according to their trust levels without invading user privacy. By utilizing the blind signature, sensing tasks are protected and reports are anonymized. In addition, a privacy-preserving credit management mechanism is introduced to achieve decentralized trust management and secure credit proof for mobile users; ii) to improve communication efficiency while guaranteeing data confidentiality, we propose a fog-assisted secure data deduplication scheme, in which a BLS-oblivious pseudo-random function is developed to enable fog nodes to detect and delete replicate data in sensing reports without exposing the content of reports. Considering the privacy leakages of mobile users who report the same data, the blind signature is utilized to hide users' identities, and chameleon hash function is leveraged to achieve contribution claim and reward retrieval for anonymous greedy mobile users; iii) to achieve data statistics with privacy preservation, we propose a privacy-preserving data statistics scheme to achieve end-to-end security and integrity protection, while enabling the aggregation of the collected data from multiple sources. The correctness verification is supported to prevent the corruption of the aggregate results during data transmission based on the homomorphic authenticator and the proxy re-signature. A privacy-preserving verifiable linear statistics mechanism is developed to realize the linear aggregation of multiple crowdsensed data from a same device and the verification on the correctness of aggregate results; and iv) to encourage mobile users to participating in sensing tasks, we propose a dual-anonymous reward distribution scheme to offer the incentive for mobile users and privacy protection for both customers and mobile users in MCS. Based on the dividable cash, a new reward sharing incentive mechanism is developed to encourage mobile users to participating in sensing tasks, and the randomization technique is leveraged to protect the identities of customers and mobile users during reward claim, distribution and deposit.

Security And Privacy In Digital Economy

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Author : Shui Yu
language : en
Publisher: Springer Nature
Release Date : 2020-10-22

Security And Privacy In Digital Economy written by Shui Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-22 with Computers categories.

This book constitutes the refereed proceedings of the First International Conference on Security and Privacy in Digital Economy, SPDE 2020, held in Quzhou, China, in October 2020*. The 49 revised full papers and 2 short papers were carefully reviewed and selected from 132 submissions. The papers are organized in topical sections: ​cyberspace security, privacy protection, anomaly and intrusion detection, trust computation and forensics, attacks and countermeasures, covert communication, security protocol, anonymous communication, security and privacy from social science. *The conference was held virtually due to the COVID-19 pandemic.

Mobile Crowdsensing And Remote Sensing In Smart Cities

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Author : Chaker Abdelaziz Kerrache
language : en
Publisher: Springer Nature
Release Date : 2024-12-27

Mobile Crowdsensing And Remote Sensing In Smart Cities written by Chaker Abdelaziz Kerrache and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Technology & Engineering categories.

This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations. Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities; Covers technical details of remote sensing starting from the communication support to the application; Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.

Privacy Preservation In Distributed Systems

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Author : Guanglin Zhang
language : en
Publisher: Springer Nature
Release Date : 2024-05-30

Privacy Preservation In Distributed Systems written by Guanglin Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-30 with Technology & Engineering categories.

This book provides a discussion of privacy in the following three parts: Privacy Issues in Data Aggregation; Privacy Issues in Indoor Localization; and Privacy-Preserving Offloading in MEC. In Part 1, the book proposes LocMIA, which shifts from membership inference attacks against aggregated location data to a binary classification problem, synthesizing privacy preserving traces by enhancing the plausibility of synthetic traces with social networks. In Part 2, the book highlights Indoor Localization to propose a lightweight scheme that can protect both location privacy and data privacy of LS. In Part 3, it investigates the tradeoff between computation rate and privacy protection for task offloading a multi-user MEC system, and verifies that the proposed load balancing strategy improves the computing service capability of the MEC system. In summary, all the algorithms discussed in this book are of great significance in demonstrating the importance of privacy.

Mobile Crowdsourcing

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Author : Jie Wu
language : en
Publisher: Springer Nature
Release Date : 2023-07-16

Mobile Crowdsourcing written by Jie Wu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-16 with Computers categories.

This book offers the latest research results in recent development on the principles, techniques and applications in mobile crowdsourcing. It presents state-of-the-art content and provides an in-depth overview of the basic background in this related field. Crowdsourcing involves a large crowd of participants working together to contribute or produce goods and services for the society. The early 21st century applications of crowdsourcing can be called crowdsourcing 1.0, which includes businesses using crowdsourcing to accomplish various tasks, such as the ability to offload peak demand, access cheap labor, generate better results in a timely matter, and reach a wider array of talent outside the organization. Mobile crowdsensing can be described as an extension of crowdsourcing to the mobile network to combine the idea of crowdsourcing with the sensing capacity of mobile devices. As a promising paradigm for completing complex sensing and computationtasks, mobile crowdsensing serves the vital purpose of exploiting the ubiquitous smart devices carried by mobile users to make conscious or unconscious collaboration through mobile networks. Considering that we are in the era of mobile internet, mobile crowdsensing is developing rapidly and has great advantages in deployment and maintenance, sensing range and granularity, reusability, and other aspects. Due to the benefits of using mobile crowdsensing, many emergent applications are now available for individuals, business enterprises, and governments. In addition, many new techniques have been developed and are being adopted. This book will be of value to researchers and students targeting this topic as a reference book. Practitioners, government officials, business organizations and even customers -- working, participating or those interested in fields related to crowdsourcing will also want to purchase this book.