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  Published Paper Details:

  Paper Title

The Decentralized Dawn: Federated Learning, Data Sovereignty, and the Trajectory of Modern Information Technology

  Authors

  Sayed Muhammed Fazil P P,  Dr.Bharathi.A

  Keywords

Distributed Machine Learning, Federated Learning, Data Sovereignty, Privacy Preserving AI, Edge Computing

  Abstract


At present, the centralized AI development method that relies on the centralization of massive, sensitive data is now confronted with technological and ethical issues brought on by the unmanageable explosion in edge data and global regulatory mandates such as GDPR and HIPAA. This paper provides a comprehensive assessment of Federated Learning (FL) as the primordial architectural approach, a distributed machine learning paradigm in which model learning is decentralized, and raw data remains compliant with the data sovereignty principle--never leaving its physical location.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2601194

  Paper ID - 300102

  Page Number(s) - b631-b637

  Pubished in - Volume 14 | Issue 1 | January 2026

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sayed Muhammed Fazil P P,  Dr.Bharathi.A,   "The Decentralized Dawn: Federated Learning, Data Sovereignty, and the Trajectory of Modern Information Technology", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.14, Issue 1, pp.b631-b637, January 2026, Available at :http://www.ijcrt.org/papers/IJCRT2601194.pdf

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Call For Paper January 2026
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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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