The Topology of Covert Conflict

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The Topology of Covert Conflict

• Shishir Nagaraja, Ross Anderson
• Cambridge University

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Topology and Resilience

• Many real-world networks can be modeled as
  scale-free social contacts, disease spread,
  spread of computer viruses
• Power-law distribution of vertex order, often
  arising from preferential attachment
• Highly-connected nodes greatly enhance
  connectivity
• This gives resilience against random failure

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Topology and Vulnerability

• Although power-law vertex order distribution
  gives resilience to random failure, it makes the
  network vulnerable to targeted attack
• If you attack high-order nodes, the network is
  rapidly disconnected (Albert, Jeong and Barabási,
  2000)
• Example Sierra Leone HIV/AIDS program treated
  prostitutes first only 2 of population
  infected (vs 40 in Botswana)

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Topology and Vulnerability (2)

• Music companies target high-order nodes in
  peer-to-peer networks (prolific uploaders)
• More traditional example if you conquer a
  country, subvert or kill the bourgeoisie first
• What about the dynamic case, e.g. insurgency?
  Police keep arresting, insurgents keep recruiting
• We set out to study this dynamic case, using
  evolutionary game theory

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Simulation Methodology

• After Axelrods work on iterated prisoners
  dilemma
• Scale-free network of 400 nodes
• At each round, attacker kills 10 nodes their
  selection is his strategy
• Defender recruits 10 more, then reconfigures
  network how he does this is his strategy
• Iterate search for defense, attack strategy

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Naïve Defenses Dont Work!

• Basic vertex-order attack network dead after 2
  rounds
• Random replenishment 3 rounds
• Scale-free replenishment 4 rounds

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Evolving Defense Strategies

• Black scalefree replenishment
• Green replace high-order nodes with rings
• Cyan - replace high-order nodes with cliques
• Cliques work very well against the vertex-order
  attack

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Evolving Attack Strategies

• Centrality attacks are the best counter we found
  to clique-based defenses
• Rings G, B cliques C, M
• Vertex-order attack B, G, C
• Attack using centrality R, B, M

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Next Evolution

• Combine two defensive strategies yellow graph
  is delegation plus cliques
• Modern terror network?
• 3rd-generation music-sharing network?

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What this teaches

• People set out to make peer-to-peer systems
  robust by arranging the nodes in rings. This
  didnt work. Clubs do work
• We have some insight into why insurgents organise
  themselves in cells
• We can model strategies for wiretapping,
  surveillance, counterinsurgency
• What about biology?

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Biological Robustness

• Redundancy via homologous genes makes an organism
  better able to evolve (phenotypic changes less
  often lethal)
• This evolvability is an important element of
  robustness (Hiroaki Kitano, Nature, Nov 2004, pp
  826837)
• What we call cells biologists think of as
  conserved clusters, the bows in bow-tie networks,
  or evolutionary capacitors
• Our work may give an insight into the evolution
  of hierarchical modularity

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Conclusion

• Weve built a bridge between network analysis and
  evolutionary game theory
• Using our simulation methodology, we get insights
  into why revolutionaries use cells, the effects
  of modern policing, and more
• Simulations let us explore many new attack and
  defense strategies
• Implications for all sorts of networks
  computer, social, political biological?