Biblio

Resilience in the information sciences is notoriously difficult to define much less to measure. But in mechanical engineering, the resilience of a substance is mathematically well-defined as an area under the stress-strain curve. We combined inspiration from mechanics of materials and axioms from queuing theory in an attempt to define resilience precisely for information systems. We first examine the meaning of resilience in linguistic and engineering terms and then translate these definitions to information sciences. As a general assessment of our approach's fitness, we quantify how resilience may be measured in a simple queuing system. By using a very simple model we allow clear application of established theory while being flexible enough to apply to many other engineering contexts in information science and cyber security. We tested our definitions of resilience via simulation and analysis of networked queuing systems. We conclude with a discussion of the results and make recommendations for future work.
 

Many common cyberdefenses (like firewalls and intrusion-detection systems) are static, giving attackers the freedom to probe them at will. Moving-target defense (MTD) adds dynamism, putting the systems to be defended in motion, potentially at great cost to the defender. An alternative approach is a mobile resilient defense that removes attackers' ability to rely on prior experience without requiring motion in the protected infrastructure. The defensive technology absorbs most of the cost of motion, is resilient to attack, and is unpredictable to attackers. The authors' mobile resilient defense, Ant-Based Cyber Defense (ABCD), is a set of roaming, bio-inspired, digital-ant agents working with stationary agents in a hierarchy headed by a human supervisor. ABCD provides a resilient, extensible, and flexible defense that can scale to large, multi-enterprise infrastructures such as the smart electric grid.

Cover time measures the time (or number of steps) required for a mobile agent to visit each node in a network (graph) at least once. A short cover time is important for search or foraging applications that require mobile agents to quickly inspect or monitor nodes in a network, such as providing situational awareness or security. Speed can be achieved if details about the graph are known or if the agent maintains a history of visited nodes, however, these requirements may not be feasible for agents with limited resources, they are difficult in dynamic graph topologies, and they do not easily scale to large networks. This paper introduces a set-based form of heading (directional bias) that allows an agent to more efficiently explore any connected graph, static or dynamic. When deciding the next node to visit, agents are discouraged from visiting nodes that neighbor both their previous and current locations. Modifying a traditional movement method, e.g., random walk, with this concept encourages an agent to move toward nodes that are less likely to have been previously visited, reducing cover time. Simulation results with grid, scale-free, and minimum distance graphs demonstrate heading can consistently reduce cover time as compared to non-heading movement techniques.