Tutorial: Secure Multiparty Computation for Cloud Computing Paradigm by Durgesh Kumar Mishra

Abstract

Secure Multiparty Computation (SMC) allows multiple parties to perform computation on their private data to evaluate some function of their common interest. In this paradigm the individual data should be kept secret from other parties and the result of the computation should be available to all the parties. This subject of information security has created enormous interest among researchers. Many SMC models were devised and analyzed. The subject is becoming more relevant in this scenario of huge online transactions on the Internet. Many solutions, from earlier Millionaires Problem to recent Anonymity based computation on encrypted data are available in the literature. Cloud Computing is a paradigm shift from the distributed computing where an organization uses resources as service. This is a sort of “utility computing” where you pay-as-you-go like electricity bill. Cloud providers are the companies which manage large datacenters and have expertise of operating these datacenters. Cloud users are the organizations which use services from providers. Cloud users need not to deploy computing resources at their site. These resources are available from the cloud providers on utility basis and charged on usage basis. Thus an organization can improve efficiency while minimizing the expenditure and the operation overhead. They can focus on their core competencies. In this paradigm users send their data to the provider for computation and the result is provided by the provider. Many companies like Amazon, Google, IBM etc. are already in the market working as the cloud provider. As the services are gaining more popularity, concerns regarding the privacy of these data are also arising. They users of the cloud are worrying about the privacy of their data that has been supplied to the cloud provider. The solutions to these problems can be provided by the protocols of the SMC. In this tutorial, we propose SMC solution techniques that can be embedded while designing architecture of cloud computing especially when multiple cloud providers or multiple cloud users jointly compute some function of their private data inputs. Each of the users or providers of the cloud is worried about the privacy of the individual data but due to the mutual interest all of them want to know the value of the common function. With our experience of developing protocols and devising algorithms for various SMC problems we anticipate a crucial role of SMC in cloud computing. For example consider a case where multiple cloud users jointly work on a project and utilize the services of the same cloud provider. All of them want to simultaneously evaluate their equations