  Internet measurements are a crucial foundation of IPv6-related research. Due
to the infeasibility of full address space scans for IPv6 however, those
measurements rely on collections of reliably responsive, unbiased addresses, as
provided e.g., by the IPv6 Hitlist service. Although used for various use
cases, the hitlist provides an unfiltered list of responsive addresses, the
hosts behind which can come from a range of different networks and devices,
such as web servers, customer-premises equipment (CPE) devices, and Internet
infrastructure. In this paper, we demonstrate the importance of tailoring
hitlists in accordance with the research goal in question. By using PeeringDB
we classify hitlist addresses into six different network categories, uncovering
that 42% of hitlist addresses are in ISP networks. Moreover, we show the
different behavior of those addresses depending on their respective category,
e.g., ISP addresses exhibiting a relatively low lifetime. Furthermore, we
analyze different Target Generation Algorithms (TGAs), which are used to
increase the coverage of IPv6 measurements by generating new responsive targets
for scans. We evaluate their performance under various conditions and find
generated addresses to show vastly differing responsiveness levels for
different TGAs.
