Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/499752
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2023-07-18T04:52:49Z | - |
dc.date.available | 2023-07-18T04:52:49Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/499752 | - |
dc.description.abstract | With the expansion of the Internet of Things (IoT) and the crowdsensing model, as a new developing IoT application that utilizes users with intelligent devices everywhere for data sensing and processing. Data-driven products depend primarily on the Mobile Crowd Sensing (MCS) model, which relies on mobile phone or mobile device users to collect the needed data, which helps to make any business decisions or for a societal benefit. MCS collects an immense amount of information from several accessible nodes at a lower cost to provide effective performance. MCS is a pervasive model that combines individuals in the crowd and collects data, which are further shared to measure or monitor events of general concern using devices. Integrated with intrinsic mobility and intellectuality, mobile users can acquire, make and transmit massive amounts of data to the Centralized Service Provider based on the data sensed by MCS. Compared with conventional sensor networks, the MCS can maintain large-scale sensing models, enhance data integrity and minimize the cost of products to improve the data quality newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | A Blockchain Based Decentralized Data Privacy and Security Model for Crowd Sensing Networks | |
dc.title.alternative | ||
dc.creator.researcher | Arulprakash, M | |
dc.subject.keyword | Automation and Control Systems | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | Jebakumar, R | |
dc.publisher.place | Kattankulathur | |
dc.publisher.university | SRM Institute of Science and Technology | |
dc.publisher.institution | Department of Computer Science Engineering | |
dc.date.registered | ||
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 178.56 kB | Adobe PDF | View/Open |
02_preliminary page.pdf.pdf | 338.08 kB | Adobe PDF | View/Open | |
03_content.pdf | 217.89 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 172.96 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 690.15 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 406.64 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 782.7 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.28 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.45 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 193.12 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 361.38 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 238.25 kB | Adobe PDF | View/Open |
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