  Active Internet measurement studies rely on a list of targets to be scanned.
While probing the entire IPv4 address space is feasible for scans of limited
complexity, more complex scans do not scale to measuring the full Internet.
Thus, a sample of the Internet can be used instead, often in form of a "top
list". The most widely used list is the Alexa Global Top1M list. Despite their
prevalence, use of top lists is seldomly questioned. Little is known about
their creation, representativity, potential biases, stability, or overlap
between lists. As a result, potential consequences of applying top lists in
research are not known. In this study, we aim to open the discussion on top
lists by investigating the aptness of frequently used top lists for empirical
Internet scans, including stability, correlation, and potential biases of such
lists.
