Data Privacy and Cybersecurity in Mobile Crowdsensing
Mobile crowdsensing (MCS) has emerged as a pivotal element in contemporary communication technology, witnessing substantial growth recently. The advent of 5G, the Internet of Things (IoT), and edge computing has propelled MCS researchers to achieve enhanced sensing efficiency and broaden its applica...
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| 格式: | Online |
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| 語言: | 英语 |
| 出版: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| 主題: | |
| 在線閱讀: | ONIX_20250812T110751_9783725845408_534 |
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| _version_ | 1869516930024472576 |
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| collection | Directory of Open Access Books |
| description | Mobile crowdsensing (MCS) has emerged as a pivotal element in contemporary communication technology, witnessing substantial growth recently. The advent of 5G, the Internet of Things (IoT), and edge computing has propelled MCS researchers to achieve enhanced sensing efficiency and broaden its application spectrum across various domains such as environmental monitoring, traffic management, and healthcare. However, despite these advantages, MCS confronts significant security and privacy challenges due to its open and diverse nature. Critical concerns encompass data leakage, unauthorized access, data tampering, and cross-network attacks. These issues can severely compromise the stability, privacy, and security of MCS systems. Furthermore, the dynamic mobility of users and devices within MCS introduces additional complexity to conventional security measures, particularly concerning communication and cross-domain access control. To tackle these challenges, researchers have devised several strategies aimed at bolstering the security and privacy of MCS systems. These novel protection mechanisms offer distinct benefits over traditional approaches. They are capable of securing data even with constrained computational and communication resources, enhancing system flexibility, and effectively thwarting sophisticated cyberattacks. These strategies provide both theoretical and practical underpinnings for fortifying MCS security and lay a robust foundation for the field’s future evolution. |
| format | Online |
| id | doab-20.500.12854ir-165779 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1657792025-08-12T10:16:08Z Data Privacy and Cybersecurity in Mobile Crowdsensing Zhang, Chuan Wu, Tong Zhang, Weiting mobile crowdsensing privacy preservation cybersecurity data collection task allocation datasharing data analysis user incentive thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Mobile crowdsensing (MCS) has emerged as a pivotal element in contemporary communication technology, witnessing substantial growth recently. The advent of 5G, the Internet of Things (IoT), and edge computing has propelled MCS researchers to achieve enhanced sensing efficiency and broaden its application spectrum across various domains such as environmental monitoring, traffic management, and healthcare. However, despite these advantages, MCS confronts significant security and privacy challenges due to its open and diverse nature. Critical concerns encompass data leakage, unauthorized access, data tampering, and cross-network attacks. These issues can severely compromise the stability, privacy, and security of MCS systems. Furthermore, the dynamic mobility of users and devices within MCS introduces additional complexity to conventional security measures, particularly concerning communication and cross-domain access control. To tackle these challenges, researchers have devised several strategies aimed at bolstering the security and privacy of MCS systems. These novel protection mechanisms offer distinct benefits over traditional approaches. They are capable of securing data even with constrained computational and communication resources, enhancing system flexibility, and effectively thwarting sophisticated cyberattacks. These strategies provide both theoretical and practical underpinnings for fortifying MCS security and lay a robust foundation for the field’s future evolution. 2025-08-12T10:16:06Z 2025-08-12T10:16:06Z 2025 book ONIX_20250812T110751_9783725845408_534 9783725845408 9783725845392 https://directory.doabooks.org/handle/20.500.12854/165779 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/11242 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4539-2 10.3390/books978-3-7258-4539-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725845408 9783725845392 454 open access |
| spellingShingle | mobile crowdsensing privacy preservation cybersecurity data collection task allocation datasharing data analysis user incentive thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Data Privacy and Cybersecurity in Mobile Crowdsensing |
| title | Data Privacy and Cybersecurity in Mobile Crowdsensing |
| title_full | Data Privacy and Cybersecurity in Mobile Crowdsensing |
| title_fullStr | Data Privacy and Cybersecurity in Mobile Crowdsensing |
| title_full_unstemmed | Data Privacy and Cybersecurity in Mobile Crowdsensing |
| title_short | Data Privacy and Cybersecurity in Mobile Crowdsensing |
| title_sort | data privacy and cybersecurity in mobile crowdsensing |
| topic | mobile crowdsensing privacy preservation cybersecurity data collection task allocation datasharing data analysis user incentive thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | mobile crowdsensing privacy preservation cybersecurity data collection task allocation datasharing data analysis user incentive thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20250812T110751_9783725845408_534 |