Information Security as Strategic (In)effectivity

Security of information flow is commonly understood as preventing any information leakage, regardless of how grave or harmless consequences the leakage can have. In this work, we suggest that information security is not a goal in itself, but rather a means of preventing potential attackers from compromising the correct behavior of the system. To formalize this, we first show how two information flows can be compared by looking at the adversary's ability to harm the system. Then, we propose that the information flow in a system is effectively information-secure if it does not allow for more harm than its idealized variant based on the classical notion of noninterference

Markov modeling of moving target defense games

We introduce a Markov-model-based framework for Moving Target Defense (MTD) analysis. The framework allows modeling of broad range of MTD strategies, provides general theorems about how the probability of a successful adversary defeating an MTD strategy is related to the amount of time/cost spent by the adversary, and shows how a multi-level composition of MTD strategies can be analyzed by a straightforward combination of the analysis for each one of these strategies. Within the proposed framework we define the concept of security capacity which measures the strength or effectiveness of an MTD strategy: the security capacity depends on MTD specific parameters and more general system parameters. We apply our framework to two concrete MTD strategies

Evolving Robocode Tank Fighters

In this paper, I describe the application of genetic programming to evolve a controller for a robotic tank in a simulated environment. The purpose is to explore how genetic techniques can best be applied to produce controllers based on subsumption and behavior oriented languages such as REX. As part of my implementation, I developed TableRex, a modification of REX that can be expressed on a fixed-length genome. Using a fixed subsumption architecture of TableRex modules, I evolved robots that beat some of the most competitive hand-coded adversaries