Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/576282
Title: | Intelligent Trust Management Framework for Social IoT using Machine Learning |
Researcher: | Kaur, Amandeep |
Guide(s): | Sahu, Rakesh and Anand, Darpan |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | Chandigarh University |
Completed Date: | 2023 |
Abstract: | The continuous improvement in computing and communication technologies leads newlineto the generation of smart objects that can sense, process, and communicate data. newlineThese smart objects called Things, is an essential component that is used in Internet of Things (IoT). Further, IoT is merged with the field of Social Networking lead newlinetowards subdomain called Social IoT. It allows the objects to create their social networks like humans that will help to solve the computational and other problems in newlinecollaborative manner. It employees different architecture for connectivity of objects newlineand social network with context intelligence. The importance of exchange of data newlineamong the social objects and other computational tasks leads towards the need to newlineempathize on trustworthiness of the social objects. It leads towards newline |
Pagination: | xiii, 90P. |
URI: | http://hdl.handle.net/10603/576282 |
Appears in Departments: | Department of Computer Science Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 81.9 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.07 MB | Adobe PDF | View/Open | |
03_content.pdf | 30.95 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 28.27 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 984.35 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 160.36 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.24 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 965.89 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 25.21 kB | Adobe PDF | View/Open | |
10_annexures.pdf | 90.5 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 101.52 kB | Adobe PDF | View/Open |
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