  Inspired by scenarios where the strategic network design and defense or
immunisation are of the central importance, Goyal et al. [3] defined a new
Network Formation Game with Attack and Immunisation. The authors showed that
despite the presence of attacks, the game has high social welfare properties
and even though the equilibrium networks can contain cycles, the number of
edges is strongly bounded. Subsequently, Friedrich et al. [10] provided a
polynomial time algorithm for computing a best response strategy for the
maximum carnage adversary which tries to kill as many nodes as possible, and
for the random attack adversary, but they left open the problem for the case of
maximum disruption adversary. This adversary attacks the vulnerable region that
minimises the post-attack social welfare. In this paper we address our efforts
to this question. We can show that computing a best response strategy given a
player u and the strategies of all players but u, is polynomial time solvable
when the initial network resulting from the given strategies is connected. Our
algorithm is based on a dynamic programming and has some reminiscence to the
knapsack-problem, although is considerably more complex and involved.
