Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/519702
Full metadata record
DC FieldValueLanguage
dc.coverage.spatialArtificial intelligence based secured third party authentication using blockchain in virtual private network
dc.date.accessioned2023-10-22T05:41:47Z-
dc.date.available2023-10-22T05:41:47Z-
dc.identifier.urihttp://hdl.handle.net/10603/519702-
dc.description.abstractThe evolution of the digital era and the rise of cloud computing have attracted most IT applications to migrate from physical infrastructure-based applications to cloud-based applications. Cloud computing has become an inevitable paradigm, offers uninterrupted service to the users, and possesses a most desirable feature of access from anywhere and from any device. The most common cloud-based application is the execution of third-party financial transactions over the Virtual Private Network (VPN). Online financial transactions contribute to the Gross Domestic Product (GDP) by about 7.7%. The major challenge of financial transactions through the virtual private network is its security concern, as it has often been proven vulnerable to security attacks by hackers. Numerous security breaches have been reported worldwide, motivating the research on introducing a secure channel for performing transactions in the virtual private network. newlineThe research work was initiated by introducing a Multi-Factor Authentication (MFA) framework encompassing multiple credentials like low entropy passwords and features extracted from the authenticated userand#8223;s voice print and fingerprint. The authentication credentials were encrypted and decrypted using Elliptical Curve Cryptography (ECC) and achieved a high level of security than the existing frameworks for third-party financial transactions. The key generated from the user voice print employs the enhanced Mel Frequency Cepstrum Coefficient (e-MFCC) technique, which is a significant robustness factor in the proposed research work. newline newline
dc.format.extentxxii,179p.
dc.languageEnglish
dc.relationp.160-178
dc.rightsuniversity
dc.titleArtificial intelligence based secured third party authentication using blockchain in virtual private network
dc.title.alternative
dc.creator.researcherPrabakaran, D
dc.subject.keywordcloud computing
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEngineering and Technology
dc.subject.keywordinevitable paradigm
dc.subject.keywordIT applications
dc.description.note
dc.contributor.guideShyamala, R
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions21 c m
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File164.87 kBAdobe PDFView/Open
02_prelim pages.pdf3.26 MBAdobe PDFView/Open
03_contents.pdf316.33 kBAdobe PDFView/Open
04_abstracts.pdf299.52 kBAdobe PDFView/Open
05_chapter 1.pdf623.03 kBAdobe PDFView/Open
06_chapter 2.pdf560.04 kBAdobe PDFView/Open
07_chapter 3.pdf1.05 MBAdobe PDFView/Open
08_chapter 4.pdf1 MBAdobe PDFView/Open
09_chapter 5.pdf927.38 kBAdobe PDFView/Open
10_chapter 6.pdf983.75 kBAdobe PDFView/Open
11_chapter 7.pdf857.35 kBAdobe PDFView/Open
12_annexures.pdf229.53 kBAdobe PDFView/Open
80_recommendation.pdf174.41 kBAdobe PDFView/Open


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: