  The Internet and social media have fueled enormous interest in social network
analysis. New tools continue to be developed and used to analyse our personal
connections, with particular emphasis on detecting communities or identifying
key individuals in a social network. This raises privacy concerns that are
likely to exacerbate in the future. With this in mind, we ask the question: Can
individuals or groups actively manage their connections to evade social network
analysis tools?
  By addressing this question, the general public may better protect their
privacy, oppressed activist groups may better conceal their existence, and
security agencies may better understand how terrorists escape detection. We
first study how an individual can evade "network centrality" analysis without
compromising his or her influence within the network. We prove that an optimal
solution to this problem is hard to compute. Despite this hardness, we
demonstrate that even a simple heuristic, whereby attention is restricted to
the individual's immediate neighbourhood, can be surprisingly effective in
practice. For instance, it could disguise Mohamed Atta's leading position
within the WTC terrorist network, and that is by rewiring a strikingly-small
number of connections. Next, we study how a community can increase the
likelihood of being overlooked by community-detection algorithms. We propose a
measure of concealment, expressing how well a community is hidden, and use it
to demonstrate the effectiveness of a simple heuristic, whereby members of the
community either "unfriend" certain other members, or "befriend" some
non-members, in a coordinated effort to camouflage their community.
