  Social network analysis tools can infer various attributes just by
scrutinizing one's connections. Several researchers have studied the problem
faced by an evader whose goal is to strategically rewire their social
connections in order to mislead such tools, thereby concealing their private
attributes. However, to date, this literature has only considered static
networks, while neglecting the more general case of temporal networks, where
the structure evolves over time. Driven by this observation, we study how the
evader can conceal their importance from an adversary armed with temporal
centrality measures. We consider computational and structural aspects of this
problem: Is it computationally feasible to calculate optimal ways of hiding? If
it is, what network characteristics facilitate hiding? This topic has been
studied in static networks, but in this work, we add realism to the problem by
considering temporal networks of edges changing in time. We find that it is
usually computationally infeasible to find the optimal way of hiding. On the
other hand, by manipulating one's contacts, one could add a surprising amount
of privacy. Compared to static networks, temporal networks offer more
strategies for this type of manipulation and are thus, to some extent, easier
to hide in.
