On the Internet we constantly receive offers of goods and services that could potentially be of interest to us. These recommendations are created based on online profiles, search queries, network activity, and t. Sometimes these suggestions are really useful, but by clicking on such links, the user risks confidentiality because it confirms the transfer of personal data. Mahsa Taziki from the Federal Polytechnic School of Lausanne came up with an algorithm that solves this problem.

The developed algorithm is able to determine in real time the amount of information transferred to third parties when clicking on a particular link with the recommended product on the Internet.

"80% of clicks provide a trade-off between utility and privacy for users. Some clicks are very useful and do not compromise your privacy, while others are completely opposite. My goal is to accurately calculate the utility and risk of privacy from user clicks. People will be able to decide what to push them for, and service providers - use it to improve their products, "said Mahsa Taziki.

The algorithm examines each potential click, estimating the amount of data sent, the potential impact on privacy and what the user receives in return. Results are suggested in the form of tips, allowing a person to quickly decide whether to click on a message.

"Ultimately, we want everyone to be free to take advantage of online recommendations while maintaining maximum control over their confidentiality and the data that they share," said Mahsa Taziki.