2008/12/22 by Marios Mavronicolas, Burkhard Monien, Mavronicolas, Marios +3
Computer Science · Decision Sciences · Physics and Astronomy · #Complex Network Analysis Techniques #Game Theory and Applications #Information and Cyber Security #cs.GT
paper · pdf · doi:10.48550/arxiv.0812.4206
arxiv created 2008/12/22 · arxiv updated 2009/12/01
In a distributed system with \it attacks and \it defenses, both \it attackers and \it defenders are self-interested entities. We assume a \it reward-sharing scheme among \it interdependent defenders; each defender wishes to (locally) maximize her own total \it fair share to the attackers extinguished due to her involvement (and possibly due to those of others). What is the \em maximum amount of protection achievable by a number of such defenders against a number of attackers while the system is in a \it Nash equilibrium? As a measure of system protection, we adopt the \it Defense-Ratio \citeMPPS05a, which provides the expected (inverse) proportion of attackers caught by the defenders. In a \it Defense-Optimal Nash equilibrium, the Defense-Ratio is optimized. We discover that the possibility of optimizing the Defense-Ratio (in a Nash equilibrium) depends in a subtle way on how the number of defenders compares to two natural graph-theoretic thresholds we identify. In this vein, we obtain, through a combinatorial analysis of Nash equilibria, a collection of trade-off results: - When the number of defenders is either sufficiently small or sufficiently large, there are cases where the Defense-Ratio can be optimized. The optimization problem is computationally tractable for a large number of defenders; the problem becomes \cal NP-complete for a small number of defenders and the intractability is inherited from a previously unconsidered combinatorial problem in \em Fractional Graph Theory. - Perhaps paradoxically, there is a middle range of values for the number of defenders where optimizing the Defense-Ratio is never possible.