Secure and Privacy Preserving Data Processing Frameworks for Large Scale Cloud Based Systems
Keywords:
Cloud Computing, Privacy Preservation, Secure Data Processing, Homomorphic Encryption, Differential Privacy, Data Confidentiality, Multi-Tenant Security, Cryptographic FrameworksSynopsis
As the volume of data generated and processed in cloud-based systems escalates, the need for secure and privacy-preserving data processing frameworks has become imperative. This paper explores modern cryptographic and architectural solutions that allow for confidentiality, integrity, and compliance in large-scale distributed environments. We present a comprehensive overview of state-of-the-art methodologies, assess current implementation models, and propose a framework for scalable, secure data computation. Through performance metrics and comparative analysis, this study contributes to the identification of promising frameworks suitable for industrial applications.
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