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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Data security model using deep learning and edge computing for Internet of Things (IoT) in smart city

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    17201019, 17301149, 17101432, 17301008, 17301127_CSE.pdf (2.951Mb)
    Date
    2021-09
    Publisher
    Brac University
    Author
    Aziz, Md. Yasin
    Kabbo, Tanjid Alam
    Tahsin, Tasnuva
    Zumme, Nadia Haque
    Tahsin, Mohammad Sadman
    Metadata
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    URI
    http://hdl.handle.net/10361/15756
    Abstract
    In the current ongoing world of the IoT (Internet of Things) devices, it is absolutely vital to have a safe, secure and reliable cyberspace. A cyberspace or network where it is free from all sorts of unethical activities like hacked systems, data breaches and stolen data. For that, goal to be accomplished we need to have a modern, strong and rigid cybersecurity system so that the information and data stays safe from threats and attacks. Our conducted research includes recent IoT data security issues and a robust security model which ensures the data security of the IoT devices based on a smart city's perspective. According to the recent research data on the vulnerable IoT devices we propose an intelligent and effective security approach to tackle the modern IoT security issues because our data needs to be protected as the IoT devices or \things" as we call it needs to have proper security. A few areas of future research indicate the use of blockchain to resolve the cybersecurity issues of the IoT devices are the most promising and interesting.
    Keywords
    IoT; CNN; LSTM; Edge computer; Smart city; Malware; Internet; Security; IoT device
     
    LC Subject Headings
    Internet of things; Computer networks--Security measures; Cognitive learning theory
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 25-27).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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