Secrecy and Privacy of Sensitive Data in Multiparty Computations in Joint Ventures

In data science computations there is a continuous growth of data. With such a large scale growth of data, a need to privacy and security of the data is essentially considered. Such growth of data is also due to increase in services on offer by many private sector business providers. In recent years many technique were floated to deal with control the security threat to an organization. There are many trigonometric functions that generate multiple valued characteristics. This essentially generates two or more than two values for every object in data base. This preprocessing is used for a data set before subjecting it to latest technology of Artificial neural network, fuzzy logic and data mining supervised or unsupervised learning. In the current research simulations have been performed on without compromising intended business.