SOSQRT: Efficient Secure Outsourcing Protocol for Square Root Computation

Cloud computing has emerged as a critical solution for handling large-scale computations, offering powerful resources and scalability. However, outsourcing computations to the cloud introduces significant privacy concerns, as sensitive data might be exposed during processing. To address these challenges, secure outsourcing protocols have been developed, ensuring that data privacy is maintained during remote computations. Despite their potential, existing secure outsourcing protocols have limitations in the variety of operations they support, restricting their applicability in real-world scenarios. In this paper, we propose SOSQRT, an efficient and secure outsourcing protocol for square root computation. We employ an innovative area approximation technique to compute square roots accurately while minimizing computational overhead. To protect user privacy throughout the process, we integrate three secure protocols-SCMP, SMUL, and SDIV-to ensure data confidentiality during remote execution. Additionally, our design optimizes the protocol's performance, achieving reduced time and communication costs compared to existing solutions. Experimental results demonstrate the effectiveness of SOSQRT, showing significant improvements in computational efficiency and privacy protection.