My first foray into cyber security was a study of how to control virus outbreaks within a network. There has been a considerable amount of work done on how contagion spreads through a network; however, there is been much less work on how to design control strategies based on a network’s topology. One of my former Ph.D. students and I developed a compact integer programming formulation along with several heuristics for determining the links to block in a social network in order to minimize the number of connections between susceptible and infected persons.

I have also performed research on modeling cyber networks using a concept called an attack graph along with approaches for optimizing the allocation of resources to protect the graph. Our team has developed an approach that models a two-player game on the graph as a bi-level integer program with a binary inner problem. To overcome the non-convexity in the inner problem, we developed a customized solution approach. We have continued this work by including the concepts of bounded rationality; in addition, another Ph.D. student has incorporated conditional value-at-risk into the model.

In addition, I have also begun to develop big data analytic approaches for cyber security, focus on large-scale graph analytics. This work has been funded by the Pacific Northwest National Laboratory.

Selected Publications

  1. An optimized resource allocation approach to identify and mitigate supply chain risks using fault-tree analysis
    Sherwin, M., Brown, K. J., Medal, H., and Mackenzie, C.. IISE Transactions 52(2). to appear, 236–254.
    Publication Year: 2020
    Abstract
  2. A Model-Based Systems Engineering Approach to Critical Infrastructure Vulnerability Assessment and Decision Analysis
    Huff, J. D., Medal, H., and K. A. Griendling. Submitted to Systems Engineering 22(2), 114–133.
    Publication Year: 2019
    [Link to Article] Abstract
  3. NATO Human View Executable Architectures for Critical Infrastructure Analysis
    Huff, J. D., Leonard, W., B. Smith, K. Griendling, and Medal, H.. Engineering Management Journal. 31:4, 224-245.
    Publication Year: 2019
    [Link to Article] Abstract
  4. Proactive Cost-Effective Risk Mitigation in a Low Volume High Value Supply Chain Using Fault-Tree Analysis
    Michael D. Sherwin, Hugh Medal, Steven A. Lapp. International Journal of Production Economics, Volume 175, Pages 153–163
    Publication Year: 2016
    [PDF]   [Link to Article] Abstract
  5. A Bi-objective Analysis of the R-All-Neighbor P-Center Problem
    Hugh R. Medal, Chase E. Rainwater, Edward A. Pohl, Manuel D. Rossetti. Computers & Industrial Engineering, Volume 72, Pages 114–128
    Publication Year: 2014
    [PDF]   [Link to Article] Abstract
  6. A Multi-objective Integrated Facility Location-Hardening Model: Analyzing the Pre- and Post-Disruption Tradeoff
    Hugh R. Medal, Edward A. Pohl, Manuel D. Rossetti. European Journal of Operational Research, Volume 237, 257– 270
    Publication Year: 2014
    [PDF]   [Link to Article] Abstract
  7. Robust Facility Location: Hedging Against Failures
    Ivan Hernandez, Jose Emmanuel Ramirez-Marquez, Chase Rainwater, Edward Pohl, Hugh Medal. Reliability Engineering & System Safety, Volume 123, Pages 73–80
    Publication Year: 2014
    [PDF]   [Link to Article] Abstract
  8. Vulnerability Assessment and Re-routing of Freight Trains Under Disruptions: A Coal Supply Chain Network Application
    Ridvan Gedik, Hugh Medal, Chase Rainwater, Ed A. Pohl, Scott J. Mason. Transportation Research Part E, Volume 71, 45–57
    Publication Year: 2014
    [PDF]   [Link to Article] Abstract
  9. Models for reducing the risk of critical networked infrastructures
    Hugh Medal, Stevenson J. Sharp, Ed Pohl, Chase Rainwater, Scott J. Mason. International Journal of Risk Assessment and Management, Volume 15 (No. 2/3), Pages 99-127
    Publication Year: 2011
    [PDF]   [Link to Article] Abstract

Funding

Large-Scale graph analytics for cyber network vulnerability analysis

Agency: Pacific Northwest National Laboratory (via the Distributed Analytics and Security Institute)
Researchers: Medal, H.R. (PI), Bian, L., Hu, M., Marufuzzaman, M., Zhang, S.
Amount: $600,000
Abstract

The main goal of this project is to develop a new cyber-node classification approach that utilizes both graph theory and probability modeling. We will pursue our project goal via four objectives: 1) develop an ensemble of models for the probability that a node is malicious or compromised and that an edge exists or not; 2) use advanced model selection techniques to recommend the best probability model; 3) develop novel graph analytic methods that can incorporate uncertainty and scale up to solve very large datasets, and 4) develop new approaches for computing graph uncertainty.