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Supercomputing Challenge

Internet Weakness Analysis

Team: 53

School: LOS ALAMOS HIGH

Area of Science: Computer Science

Interim:

Team 53 Interim Report

Team Members:

Kirat Pandya
Calvin Loncaric
Paolo Venneri
Gabe Vigil
Coleson Ruminer

Problem Definition

The internet has grown and most of today's worldwide commerce is based on it. Terrorist of the future will be "cyber terrorists", taking down important nodes on the internet, thereby debilitating large sections of the network. The internet is a godsend for those who are involved in intelligence activity. But the expansion of information technology also poses a threat. Terrorist networks, such as Al-Qaida, can easily get hold of detailed information. The Internet also increases the vulnerability of authorities, organizations and companies. The ability of terrorists to carry out attacks on the critical infrastructure of society may increase. The cause is the way society is developing in the area of information technology and the generally available knowledge of basic technology and methods which exists in Computer Network Intelligence (CNI). CNI here means intelligence activity where the gathering of open or secret information takes place from computer networks using computers or computer networks. As the internet spreads, network ties end up being unevenly distributed, with some areas of the network having a high density of links and other areas of the network sparsely connected. This leads to the creation of critical network nodes that handle the traffic for large subsections of the internet.

Problem Solution

The internet can be represented by Graph Theory. Graph theory is a branch of mathematics which allows for easy analysis of large networks. Unlike Euclidean geometry, in graph theory each vertex is defined only by the other vertecies it is connected to, instead of by its absolute coordinates. The position of a vertex does not matter, only its relation to other vertices. Connections between vertices are called edges. Edges may have weights, representing their importance. A higher weight means a higher importance. The problem can best be approached using the max-flow min-cut theorem, derived from Mengerâ€™s theorem. The max-flow min-cut theorem states that the maximal amount of flow is equal to the capacity of a minimal cut. In layman terms, the theorem states that the maximum flow in a network is dictated by its bottleneck. Between any two nodes, the quantity of material flowing from one to the other cannot be greater than the weakest set of links somewhere between the two nodes.

Current Progress

Our group has done significant research into graph theory. We have a good understanding of the problem at hand and are confident that we can execute the solution. We have found two mentors willing to help us. Elena Giorgi has an understanding of graph theory and has pointed us in the right direction. It was her who told us about the max-flow min-cut theorem. Kyle Fitzpatrick has told us that he is willing to assist with C/C++ and Java programming.

Expected Results

We expect that an average machine will not be able to perform the required calculations in any reasonable amount of time. The compuatation will require a very powerful computer. Our expectation is that the program will find that there will be around 10 highly important nodes which, if disconnected, will cause the greatest fragmentation of the network. These nodes will probably be the ones which have the most number of connections to other nodes.

Citations

http://en.wikipedia.org/wiki/Max-flow_min-cut_theorem
http://en.wikipedia.org/wiki/Cut_(graph_theory)
http://www.cheswick.com/ches/map/dbs/index.html

Team Members:

Sponsoring Teacher: Diane Medford