There have been many studies on malicious targeting of network nodes using degree, betweenness etc. We propose a new network metric, edge proximity, {\cal P}_e, which demonstrates the importance of specific edges in a network, hitherto not captured by existing network metrics. Effects of removing edges with high {\cal P}_e might initially seem inconspicuous but is eventually shown to be very harmful for the network. When compared to existing strategies,  removal of edges by {\cal P}_e , leads to remarkable increase of diameter and average  path length in  real and random networks till the first disconnection and  beyond. {\cal P}_e can be consistently used to rupture the network into two nearly equal parts, thus presenting a very potent strategy to greatly harm a network. Targeting by {\cal P}_e causes notable efficiency loss in US and European power grid  . {\cal P}_e identifies proteins with essential cellular functions in protein-protein interaction networks. It pinpoints regulatory neural connections and important portions of the neural and brain networks  respectively. Energy flow interactions identified by {\cal P}_e form the backbone of long food web chains. Finally, we scrutinize the potential of {\cal P}_e in edge controllability dynamics of directed networks.
 We propose a network metric, edge proximity, {\cal P}_e, which demonstrates the importance of specific edges in a network, hitherto not captured by existing network metrics. The effects of removing edges with high {\cal P}_e might initially seem inconspicuous but are eventually shown to be very harmful for networks. Compared to existing strategies, the removal of edges by {\cal P}_e leads to a remarkable increase in the diameter and average shortest path length in undirected real and random networks till the first disconnection and well beyond. {\cal P}_e can be consistently used to rupture the network into two nearly equal parts, thus presenting a very potent strategy to greatly harm a network. Targeting by {\cal P}_e causes notable efficiency loss in U.S. and European power grid networks . {\cal P}_e identifies proteins with essential cellular functions in protein-protein interaction networks. It pinpoints regulatory neural connections and important portions of the neural and brain networks , respectively. Energy flow interactions identified by {\cal P}_e form the backbone of long food web chains. Finally, we scrutinize the potential of {\cal P}_e in edge controllability dynamics of directed networks.
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There have been many studies on malicious targeting of network nodes using degree, betweenness etc.
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new
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Effects
The effects
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is
are
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the network. When compared
networks. Compared
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the
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, leads to remarkable increase of
leads to a remarkable increase in the
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shortest
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undirected
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well
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US
U.S.
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networks
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,