Backgroung: Financial services have been rapidly revolutionized using mobile cloud computing, but data privacy and scalability are a huge concern. Objective: The issue of secure and efficient data sharing in mobile clouds is addressed in this research with Secure Multi-Party Computation (SMPC) and blockchain technology for application in financial services data privacy, security, and scalability improvement. Methods: The solution is a combination of SMPC, which executes computations on ciphertext, and blockchain to ensure decentralized, transparent storage of data. The solution gives privacy and integrity of data with excellent support for scalability. Results: The system is 96.5% accurate in trust and eliminates 30% of computational overhead compared to the conventional methods. These achievements attest to the efficiency of the combined approach towards enhanced security, efficiency, and scalability. Conclusion: Merging of the SMPC and blockchain architecture guarantees an effective model of secure exchange of financial data for mobile clouds more resilient than current techniques. Large-scale processing of data can be supported in additional research with the maximum computing efficiency.

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Improving Secure Multi-party Computation and Blockchain-Enhanced Data Sharing for Financial Services in Mobile Cloud Environments

  • Rohith Reddy Mandala,
  • Narsing Rao Dyavani,
  • Bhagath Singh Jayaprakasam,
  • Charles Ubagaram,
  • Venkat Garikipati,
  • N. Purandhar

摘要

Backgroung: Financial services have been rapidly revolutionized using mobile cloud computing, but data privacy and scalability are a huge concern. Objective: The issue of secure and efficient data sharing in mobile clouds is addressed in this research with Secure Multi-Party Computation (SMPC) and blockchain technology for application in financial services data privacy, security, and scalability improvement. Methods: The solution is a combination of SMPC, which executes computations on ciphertext, and blockchain to ensure decentralized, transparent storage of data. The solution gives privacy and integrity of data with excellent support for scalability. Results: The system is 96.5% accurate in trust and eliminates 30% of computational overhead compared to the conventional methods. These achievements attest to the efficiency of the combined approach towards enhanced security, efficiency, and scalability. Conclusion: Merging of the SMPC and blockchain architecture guarantees an effective model of secure exchange of financial data for mobile clouds more resilient than current techniques. Large-scale processing of data can be supported in additional research with the maximum computing efficiency.