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Abstract : Homomorphic encryption is a transformative cryptographic technique that enables secure cloud data processing by allowing computations on encrypted data without requiring decryption. Unlike traditional encryption methods, which protect data only at rest and in transit, homomorphic encryption ensures end-to-end security, even during computation. This capability is particularly vital for industries that rely on cloud computing while handling sensitive information, such as finance, healthcare, and government sectors. However, despite its strong security guarantees, the widespread adoption of homomorphic encryption remains limited due to its high computational complexity and performance overhead. This paper examines the role of homomorphic encryption in secure cloud data processing by evaluating its advantages, challenges, and real-world applicability. First, a comprehensive literature review contrasts traditional and homomorphic encryption techniques, highlighting their security implications and efficiency trade-offs. Second, experimental simulations are conducted to assess computation time, scalability, and data transfer efficiency in cloud environments. The results underscore that while homomorphic encryption enhances data security, its feasibility depends on specific use-case requirements, balancing security, performance, and cost. Finally, we explore practical applications such as privacy-preserving data analytics and secure outsourcing of computations, demonstrating how homomorphic encryption can redefine cloud security paradigms.
Keyword Homomorphic encryption, cloud security, encrypted computation, privacy-preserving data processing, secure cloud computing.
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