Cloud computing has become one of the most popular distributed computing paradigms in recent years. With its advantages of low cost, on-demand flexibility, and high data processing abilities, more and more enterprises have adopted the cloud computing paradigm to build up their IT infrastructure. By performing collaborative computation tasks (e.g., big data analysis tasks) with multiple datasets of different correlated enterprises in cloud computing, the generated valuable information will provide the enterprises with higher productivity and financial gains. However, due to the privacy concerns from the enterprises, how to efficiently enable them to achieve secure multi-party joint datasets analysis in cloud computing without leaking their own private dataset becomes a critical but challenging problem for the enterprises. In this paper, focusing on securely performing any collaborative computation task in cloud computing, we construct a generic server-aided secure multi-party computation protocol to tackle the problem. Our solution can provide security guarantee in the setting where at most n-1 client parties are malicious while the server is semi-honest and there is no collusion between the server and clients. The security and experimental performance analysis show that this work is currently the most efficient server-aided secure multi-party computation protocol with the same security guarantee compared with all the previous works to the best of our knowledge.