Interdependent Mission Impact Assessment of an IoT System with Hypergame-Theoretic Attack-Defense Behavior Modeling
| dc.contributor.author | Thukkaraju, Ashrith Reddy | en |
| dc.contributor.committeechair | Cho, Jin-Hee | en |
| dc.contributor.committeemember | Ji, Bo | en |
| dc.contributor.committeemember | Hoang, Thang | en |
| dc.contributor.department | Computer Science and Applications | en |
| dc.date.accessioned | 2023-11-18T09:00:13Z | en |
| dc.date.available | 2023-11-18T09:00:13Z | en |
| dc.date.issued | 2023-11-17 | en |
| dc.description.abstract | Mission impact assessment (MIA) research has been explored to evaluate the performance and effectiveness of a mission system, such as enterprise networks with organizational missions and military or tactical mission teams with assigned missions. The key components in such mission systems, including assets, services, tasks, vulnerability, attacks, and defenses, are interdependent, and their impacts are interwoven. However, the current state-of-the-art MIA approaches have less studied such interdependencies. In addition, they have not modeled strategic attack-defense interactions under partial observability. In this work, we propose a novel MIA framework that assesses measures of performance (MoP) or measures of effectiveness (MoE) based on the service requirements (e.g., correctness or timeliness) of a given mission system based on full and comprehensive modeling and simulation of the key system components and their interdependencies. Particularly, we model intelligent attack-defense strategy selections based on hypergame theory, which allows considering uncertainty in estimating each player's hypergame expected utility (HEU) for its best strategy selection. As the case study, we consider an Internet-of-Things (IoT)-based mission system aiming to accurately and timely detect an object, given stringent accuracy and time constraints for successful mission completion. Via extensive simulation experiments, we validate the quality of the proposed MIA tool in its inference accuracy of the mission performance under a wide range of different environmental settings hindering the mission performance assessment and attack-defense interactions. Our results prove that the developed MIA framework shows a sufficiently high inference accuracy (e.g., 80%) even with a small portion of the training dataset (e.g., 20-50%). We also found the MIA can better assess the system's mission performance when attackers exhibit clearer patterns to take more strategic actions using hypergame theory. | en |
| dc.description.abstractgeneral | In our increasingly interconnected world, mission systems play a crucial role, whether in organizational networks or tactical military operations. We often evaluate these systems to ensure they perform effectively, but there's more to it than meets the eye. Imagine an intricate web of resources, tasks, services, assaults, and defenses that are intertwined and have an impact on one another. The strategic interactions of attack and defense in uncertain environments have been majorly ignored by conventional techniques for mission impact assessment (MIA). Our research introduces a new way of thinking about MIA. We've developed a framework that delves deep into the heart of mission systems, considering how each component affects the others. This comprehensive approach considers not just what's happening but also the interplay of actions and reactions. Hypergame theory, a technique that enables us to model intelligent choices in the face of uncertainty, is at the foundation of our approach. Imagine it as a chess game in which players must predict their opponents' moves and adjust their strategies appropriately. In our case study, we used an Internet-of-Things (IoT)-based mission system tasked with timely and accurate object detection to apply this architecture. In this mission system, both cyber attackers, whose aim is to compromise the mission, and cyber defenders, whose aim is to ensure mission success, are present, and they use the proposed hypergame-based decision-making to perform intelligent actions. What did we find? Through extensive simulations, we confirmed the effectiveness of our MIA framework. Even with limited training data, our tool demonstrated a remarkable 80% accuracy in assessing mission performance. Moreover, it excelled when attackers followed discernible patterns, allowing us to predict and respond strategically. In simpler terms, our research provides a valuable tool for evaluating the success of mission systems in our increasingly connected world. It goes beyond surface-level assessments, considering the intricate relationships between system components and the dynamic nature of strategic decision-making. Ultimately, our framework empowers us to ensure mission success in an ever-evolving landscape. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:38852 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/116674 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Mission Impact Assessment | en |
| dc.subject | mission performance | en |
| dc.subject | hypergame | en |
| dc.subject | and attack-defense interactions | en |
| dc.title | Interdependent Mission Impact Assessment of an IoT System with Hypergame-Theoretic Attack-Defense Behavior Modeling | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Computer Science and Applications | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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