Handling missing values in IP addresses and key-like features

I have a log dataset that contains +30 features. One group of these features are of the following type, for example, request_id, user_partyrole_id, authentication_id, user_login_key and such ip and key related features. I wonder what is the best way to handle missing values in such features, since IP addresses aren't numbers in the sense that we can calculate their mean value for example. To explain the context more, the data is big, +1 million rows.

Also, can someone explain how such features can be informative? The dataset is for a broadcasting company and the data records users logging from different devices to watch a match.