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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Volume 10 | Issue 9
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 112
Article Submitted : 17346
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| Paper Title: | Attacking and Protecting Data Privacy In Edge Cloud Collaborative Inferences |
| Authors Name: | Rithwik Golla , Chaithanya Jampala |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_190139
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| Published Paper Id: | IJRTI2407030 |
| Published In: | Volume 9 Issue 7, July-2024 |
| DOI: | |
| Abstract: | IoT frameworks and gadgets are turning out to be increasingly shrewd and multipurpose because of the advancement of Profound Learning innovation. In a range of Deep Learning inference tasks, it is anticipated of them that they will perform well and effectively. The dissimilarity between the confined registering force of edge gadgets and vast scope Profound Brain Organizations represents a challenge to this demand. Edge-cloud collaborative solutions, which make it possible for IoT devices with limited resources to host any Deep Learning application, then alleviate this conflict. However, when third-party clouds are employed in edge computing, privacy concerns may develop. An organized report on the chances of pursuing and protecting the security of edge-cloud cooperative frameworks is offered in this study. We have made two contributions: To get things started, we create a fresh set of assaults for a cloud that isn't trusted. These attacks can retrieve all inputs that are given instructions into the system, even if the attacker doesn't have to manipulate the data in the edge devices and protect the data. After empirically establishing that solutions that increase noise are useless against our suggested attacks, we present two more effective defense measures. This provides recommendations and expertise to boost protection by developing cooperative frameworks and calculations. |
| Keywords: | Cloud computing, Algorithms, data, defenses, security, inferences |
| Cite Article: | "Attacking and Protecting Data Privacy In Edge Cloud Collaborative Inferences", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 7, page no.288 - 290, July-2024, Available :http://www.ijrti.org/papers/IJRTI2407030.pdf |
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| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2407030
Registration ID:190139
Published In: Volume 9 Issue 7, July-2024
DOI (Digital Object Identifier):
Page No: 288 - 290 Country: Waddepally/Hanamkonda, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2407030 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2407030 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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