Enhanced Cloud File Security Using Hybrid Cryptographic Algorithms Learning

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@article{1710908,
      author = {Gaganswamy K S, Jyothi K S},
      title = {Enhanced Cloud File Security Using Hybrid Cryptographic Algorithms Learning},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {3},
      pages = {1355-1360},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710908.pdf},
      abstract = {The rapid growth of digital data and cloud-based services has created new features in ensuring confidentiality, integrity, and secure access to sensitive information. Traditional single-algorithm encryption methods often struggle to balance strong security with efficiency, leaving systems vulnerable to evolving threats. This project presents a secure file storage framework that employs a hybrid cryptography approach, combining multiple symmetric encryption algorithms?AES, ChaCha20, and Fernet?in a rotating sequence. Uploaded files are divided into smaller chunks, each protected with a different algorithm, and the corresponding keys are bundled into an encrypted key blob secured by a master key. A minimal Flask-based backend is responsible for handling the processes of encryption, decryption, and file recovery, while the user interacts through a straightforward web interface for uploading and downloading files. This design strengthens security by avoiding reliance on a single algorithm, ensuring that the data remains safeguarded even if one technique is compromised. Practical testing indicates that the proposed approach achieves an effective balance between reliability, performance, and user convenience, making it suitable for secure file storage and accessing in today?s computing environments.},
      keywords = {Hybrid Cryptography for Secure Storage, AES Chacha20 and Fernet Encryption, Cloud-Based Confidential Data Protection, Encrypted Key Management Framework, Flask Backend for File Security.},
      month = {September},
  }