Introduction to Private and Encrypted Data Science

Can we perform Data Analysis and build Machine Learning Models without revealing any information about the data and the identity of the users involved?? Every day the world is producing a lot of data and share them to different communities without thinking much about how it can use their privacy for personal vendetta, the vast amount of data is being used by various companies for to build machines which can reduce human efforts drastically using cutting-edge technologies. These data from innumerable sources is being transferred to a central server for further analysis, and hence it becomes an integral part of these communities to protect privacy as a principle that is fundamental to safeguarding the dignity and welfare of their subjects. With the advent of new GDPR/Privacy Attorney Rules, Companies are feeling a sudden need for introducing privacy and security components in existing as well as new machine learning algorithms, data storage centers and data transfer techniques as well as building secure-VM. A great emphasis now a days is on preserving identity of individuals in the data, thus providing security against various kind of data theft. Companies are investing a lot of money and time techniques which promise users that their identity and private information will be kept highly confidential, which allow users to share data without any hesitation.