User privacy risk calculator

User privacy is becoming an issue on the Internet due to common data breaches and various security threats. Services tend to require private user data in order to provide more personalized content and users are typically unaware of potential risks to their privacy. This paper proposes a risk calculator based on a feedforward neural network that will provide users with an ability to calculate risks to their privacy. The proposed calculator is evaluated on a set of real world example scenarios. Furthermore, to give more insight into privacy issues, each estimated risk is explained by several real life scenarios that might happen if the observed parameters are obtained by an attacker. In turn, this should raise user awareness and knowledge about privacy issues on the Internet.