Global infrastructure networks are the Achilles heal of the great powers. They form the basis of our wealth and our daily function yet remain extremely vulnerable. It's then little wonder that next generation terrorists, in the form of global guerrillas, will focus their efforts on the destruction of this global infrastructure. In previous posts we explored the vulnerability of scale free networks. This analysis showed that the removal of a few highly connected nodes can cause a network to fail (by dividing the network into isolated islands of connectivity). However, the analysis of dynamic networks indicates that there may be an even easier way to collapse infrastructure networks: cascading failure.

Dynamic Networks and Cascading Failures

Static maps of a network's connectivity (like a scale free network topology) don't provide a true picture of an infrastructure network's operation. Infrastructures are dynamic. There are flows of information, power, and substances constantly coursing through them. This dynamism creates a new set of vulnerabilities that can be exploited by global guerrillas. Here's how cascading network failures occur in dynamic networks when they lose high-load nodes (the loss of even a single high-load node can result in system-wide cascading failure):



Load redistribution. In most infrastructure networks, the loads carried by each node on the network are dynamically redistributed. If a network node is lost, due to accident or attack, the load that node carries is rapidly distributed to the other nodes on the network.



In most infrastructure networks, the loads carried by each node on the network are dynamically redistributed. If a network node is lost, due to accident or attack, the load that node carries is rapidly distributed to the other nodes on the network. Hi-load nodes and failure. If a high-load node is removed from the network, the loads it carries are redistributed to other nodes on the network. This increased flow causes less capable nodes to exceed their capacity. To protect these nodes from damage, many networks will automatically force the overloaded node to fail-over (shut down). In other networks, the increased congestion will cause the overloaded node to become inefficient (bog down). Regardless, the result is a series of shut-downs or slow-downs that "cascade" through the network as the excess load is pushed to the next available node. The end result is total network failure.



If a high-load node is removed from the network, the loads it carries are redistributed to other nodes on the network. This increased flow causes less capable nodes to exceed their capacity. To protect these nodes from damage, many networks will automatically force the overloaded node to fail-over (shut down). In other networks, the increased congestion will cause the overloaded node to become inefficient (bog down). Regardless, the result is a series of shut-downs or slow-downs that "cascade" through the network as the excess load is pushed to the next available node. The end result is total network failure. Heterogeneous networks. Cascading failures only occur in heterogeneous networks where there are a few nodes that have the capacity for high-loads and many with the capacity only for low-loads. Homogeneous networks, where all the nodes handle an equal load do not suffer cascading failure. Unfortunately, all infrastructure networks are heterogeneous by design.

NOTE: Cascading failures do not cleanly apply to terrorist "social" networks. In social networks, the network nodes are people and the flow is information/knowledge/etc. When a high-load node is removed, the remaining nodes will not fail due to an increase in load. People can adapt dynamically. For example: they can prioritize the new loads they inherit which mitigates the impact of a high-load node loss to the network.

Global Guerrilla Attack Planning

The vulnerability of dynamic networks to attacks on hi-load nodes is straight forward. However, planning attacks on these dynamic networks isn't. Here's how global guerrillas will plan attacks to create cascading failures within dynamic networks:



High-load node identification. There is a high level of correlation between the number of connections a node has and the amount of load it carries. Additionally, many infrastructure networks (oil, gas, electricity, etc.)concentrate production of the flow that travels through the network. In these networks, high-load nodes can be identified as those nodes that are immediately downstream from production facilities. In other networks high-load nodes are the most central (communication networks).



There is a high level of correlation between the number of connections a node has and the amount of load it carries. Additionally, many infrastructure networks (oil, gas, electricity, etc.)concentrate production of the flow that travels through the network. In these networks, high-load nodes can be identified as those nodes that are immediately downstream from production facilities. In other networks high-load nodes are the most central (communication networks). Connections instead of nodes. A non obvious approach to node failure is to attack the connections radiating from high-load nodes. The result of an attack on the connections between nodes will be the redistribution of the load carried by the damaged connection to the remaining connections. This will result in the failure of a high-load node when the remaining connections fail due to overloading (see diagram).



A non obvious approach to node failure is to attack the connections radiating from high-load nodes. The result of an attack on the connections between nodes will be the redistribution of the load carried by the damaged connection to the remaining connections. This will result in the failure of a high-load node when the remaining connections fail due to overloading (see diagram). Network suppliers. Some networks are vulnerable to undersupply (gas, electricity, and water). In these networks, an attack on a supply facility or connections from a supply facility will produce network failure as undersupplied nodes pull resources from the rest of the network (see diagram).

Source: Motter, Lai " Cascade-based attacks on Complex Networks " (PDF)