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CLOUD CLOCKING: A Privacy-Preserving Framework for Cloud Data Access Using the Data Concealment Model

  • Unique Paper ID: 180351
  • Volume: 12
  • Issue: 1
  • PageNo: 1064-1068
  • Abstract:
  • Although cloud computing offers on-demand resource access, the requirement for reliable data-handling agreements makes cross-organizational data sharing difficult. Since businesses need to have faith that others will follow the law, protecting data is essential. By hiding access patterns, this project presents the Data Concealment Model, which improves cloud data security. To differentiate real users from bots, it uses four cloaking strategies: Long-Term, Multi-Region Based, Time-Based, and Geolocation-Based Cloaking. Disguised content is sent to unauthorized users to stop intrusions. In order to hide content from unwanted access attempts, the model also employs the Camouflage Data Disguise technique, which combines Winnowing and Chaffing with ChaCha20 encryption. This method simplifies key management, provides location-aware access control, and guarantees data confidentiality. It offers a safe, privacy-focused framework for safe, seamless cloud computing by tackling fundamental data-sharing issues. smooth access to cloud data for all organizations.
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  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 1
  • PageNo: 1064-1068

CLOUD CLOCKING: A Privacy-Preserving Framework for Cloud Data Access Using the Data Concealment Model

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