Game-theoretic resource allocation for malicious packet detection in computer networks

We study the problem of optimal resource allocation for packet selection and inspection to detect potential threats in large computer networks with multiple computers of differing importance. An attacker tries to harm these targets by sending malicious packets from multiple entry points of the network; the defender thus needs to optimally allocate her resources to maximize the probability of malicious packet detection under network latency constraints. We formulate the problem as a graph-based security game with multiple resources of heterogeneous capabilities and propose a mathematical program for finding optimal solutions. We also propose Grande, a novel polynomial time algorithm that uses an approximated utility function to circumvent the limited scalability caused by the attacker's large strategy space and the non-linearity of the aforementioned mathematical program. Grande computes solutions with bounded error and scales up to problems of realistic sizes.