Enhancing And Securing Data Privacy in Cloud Through Lossless Compression and Encryption Framework

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@article{1722137,
      author = {Bala Abatcha, Ibrahim Manga, Nathan Nachandiya},
      title = {Enhancing And Securing Data Privacy in Cloud Through Lossless Compression and Encryption Framework},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {2},
      pages = {889-901},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722137.pdf},
      abstract = {As data processing and storage transition to cloud environments, maintaining a balance between efficient data compression and robust security remains a critical challenge. Traditional compression methods prioritize optimizing storage space but often neglect data protection, exposing sensitive information to security breaches. Conversely, standard encryption techniques do not reduce file sizes and can introduce high computational and bandwidth overhead during large-scale transmission.  Objective: This research proposes a secure framework that integrates Hybrid Brotli lossless data compression with AES and RSA cryptographic encryption to enhance data privacy, optimize cloud storage, and accelerate transmission speeds without sacrificing data integrity.  Methodology: Utilizing secondary data sources including academic literature, technical documentation, and performance benchmarks this study analyzes current cloud security models alongside the proposed hybrid architecture. The proposed system workflow applies deduplication and Hybrid Brotli lossless compression to user input prior to applying AES symmetric encryption for content confidentiality and RSA public-key encryption for key management. Access control is protected using OTP-based authentication before permitting decryption and lossless decompression.  Results & Significance: The comparative evaluation demonstrates that combining lossless Brotli compression with hybrid AES/RSA encryption reduces overall file sizes, conserves cloud storage space, and minimizes network bandwidth consumption compared to standalone encryption models. Furthermore, compressing data before encryption reduces the volume of information handled by cryptographic algorithms, lowering processing overhead and shortening transmission times. This framework offers an efficient, scalable, and privacy-preserving solution for managing sensitive data in cloud computing environments.},
      keywords = {AES Encryption, Cloud Computing, Data Privacy, Data Security, Hybrid Brotli, Lossless Compression, RSA Encryption.},
      month = {August},
      doi = {https://doi.org/10.64388/IREV10I2-1722137}
  }