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Data security offers storage application protection and oversight to keep highly private data and support storage infrastructures. However, an increasing problem with data privacy and security prevents the organization from using storage services. Existing privacy-protection solutions have various issues, including reliance on third parties, inadequate data privacy & accuracy, and low-performance efficiency. A novel hybrid encryption model and malware user's prediction method to enhance the data security in a storage system from unauthorized users. This proposed model is to process in two phases: Initially, the data storage process uses the hybrid Elliptic-curve-Galois Counter Mode (EC-GCM) encryption, and in the second phase: During the data accessing process, Modified Resilient Propagation (MOD-RP) neural network is utilized for the malware user prediction procedure. For evaluating the proposed model, the performance metrics such as encryption, decryption and accuracy are evaluated the outcomes are 0.007s, 0.0014s and 97.8%, respectively. The outcomes of the experiments demonstrated the effectiveness of the suggested approach in securing and protecting large amount of data in the storage system.

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Data Security and Unauthorized Access Detection Using Hybrid Encryption and Modified Attack Prediction Framework

  • 会议论文

  • 发表日期：

    2025年

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  • C. Pradeepthi,
  • K. Prasanthi,
  • V. J. VijayaGeetha,
  • B. MuniLakshmi

摘要

Data security offers storage application protection and oversight to keep highly private data and support storage infrastructures. However, an increasing problem with data privacy and security prevents the organization from using storage services. Existing privacy-protection solutions have various issues, including reliance on third parties, inadequate data privacy & accuracy, and low-performance efficiency. A novel hybrid encryption model and malware user's prediction method to enhance the data security in a storage system from unauthorized users. This proposed model is to process in two phases: Initially, the data storage process uses the hybrid Elliptic-curve-Galois Counter Mode (EC-GCM) encryption, and in the second phase: During the data accessing process, Modified Resilient Propagation (MOD-RP) neural network is utilized for the malware user prediction procedure. For evaluating the proposed model, the performance metrics such as encryption, decryption and accuracy are evaluated the outcomes are 0.007s, 0.0014s and 97.8%, respectively. The outcomes of the experiments demonstrated the effectiveness of the suggested approach in securing and protecting large amount of data in the storage system.