Secure Multi-party Computation (SMC) is a paradigm used to accomplish a common
computation among multiple users while keeping the data of each party secret from
others. In recent years there has been a keen interest among the research community
to look for techniques that can be adopted for the evolvement of SMC based solutions
for improving its e ciency and performance. Cloud computing is a next generation
computing solution in the eld of Information and Communication Technology (ICT)
which allows its users to use high speed infrastructure and services provided by Cloud
Service Providers (CSP) in a cost e ective manner with a higher availability. There-
fore, deployment of cloud based architecture for SMCs would aid in improving its
performance and e ciency. However, cloud based solutions raises concerns over secu-
rity of users' private data, since data is handled by an external party that cannot be
trusted. Hence, it is necessary to incorporate necessary security measures to ensure
the security of users' private data.
In this master's thesis we have addressed this issue by proposing a Secure Multi-
party based Cloud Computing Framework which can ensure security, privacy and
anonymity of users private data. In order to achieve this, we have formulated a case
involving sales data analysis of a certain organization through computing statistical
parameters of sales persons private sales data on a cloud environment. Furthermore,
we have implemented a prototype of the proposed security framework which aids us
to evaluate its performance. Moreover, considering the results that we have obtained,
it is conclusive that cloud platforms can be successfully deployed to improve e ciency
of SMCs while ensuring the security of users' private data; which in turn provides
evidence for the practicability of multi-party based cloud computing solutions
