Considering current trends and algorithms in data mining and machine learning, the concept digital identity is actually not so simple. Virtual identity is not just a set of parameters that are published somehow to the web, instead it is all the digital traces that are left behind by someone. It includes digital traces on google, Netflix, on different dating or music apps and so on. Currently data of such an application remains in the context of the application, however will not necessarily remain the same on a long run. As a consequence, serious data and identity leaks might occur, causing for instance that general browsing characteristic of an individual is considered at a credit or insurance evaluation.
In this sense, the privacy of an or leak of an identity will be an always increasing problem. There might be two possible answers for this problem:
1. To get the online traces of an individual independent of the identity, like with the help of private browsers, private search and other privacy tools.
2. Simulate online behavior to match an expected one with the help of online algorithmic tools, for instance with the help of bots.
