Secure Multiparty Computation in Heterogeneous Environment: Survey and Challenges

Abstract: The sharing of personal data in a distributed environment raises individual privacy concerns. However, analysis of these data may solve various real-life problems, including analysis of medical data, e-auction, secure voting, etc. Such analysis requires a system that ensures data privacy during and after computation. Secure Multi-Party Computation (MPC) is one of the popular cryptographic tools that allows a group of parties to compute a collaborative function without any personal interactions. MPC only produces the final result; it does not leak the input data or any partial results that may reveal personal information. The secret personal data of each participating party will be the input for this MPC function. In a collaborative environment, no one trusts another party but is interested in performing joint computation with their personal data. Some participating parties may be curious about others'; input to gain an advantage. Ensuring the security and privacy of individual data in such an environment, the MPC has become an emerging area of interest. Based on the application, different variants of the MPC protocols exist. The efficiency of these protocols depends on communication and computation cost, which further depends on the number of participating parties. This study demonstrates the challenges involved in developing practically implementable MPCs. The present paper reviews some existing MPC protocols based on different parameters, like security, privacy, feasibility, efficiency, number of participating parties involved in computation, and their applications. Finally, some of the best-suited MPC protocols as per their application domain have been suggested.