Companies today are leveraging more and more of user data to build models that improve their products and user experience. Companies are looking to measure user sentiments to develop products as per their need. However, this predictive capability using data can be harmful to individuals who wish to protect their privacy.

Building data models using sensitive personal data can undermine the privacy of users and can also cause damage to a person if the data gets leaked or misused. A simple solution that companies have employed for years is data anonymisation by removing personally identifiable information in datasets. But researchers have found that you can extract personal information from anonymised datasets using alternate data, something known as linkage attacks.

As anonymised data is not good enough, other techniques have been increasingly utilised by companies to preserve privacy and security of data. In this article, we will take a look at them.

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