  Network immunization is an extensively recognized issue in several domains
like virtual network security, public health and social media, to deal with the
problem of node inoculation so as to minimize the transmission through the
links existed in these networks. We aim to identify top ranked nodes to
immunize networks, leading to control the outbreak of epidemics or
misinformation. We consider group based centrality and define a heuristic
objective criteria to establish the target of key nodes finding in network
which if immunized result in essential network vulnerability. We propose a
group based game theoretic payoff division approach, by employing Shapley value
to assign the surplus acquired by participating nodes in different groups
through the positional power and functional influence over other nodes. We tag
these key nodes as Shapley Value based Information Delimiters (SVID).
Experiments on empirical data sets and model networks establish the efficacy of
our proposed approach and acknowledge performance of node inoculation to
delimit contagion outbreak.
