Impact Evaluation of Attacks on Data Flows in Systems With Heterogeneous Redundant Resources

Kosei Shimoda, Daisuke Kotani, Yasuo Okabe

Abstract: Cyber-physical and IoT systems gather diverse real-world data through systems created by heterogeneous hardware, software resources, and communication technologies, which introduce various threats and countermeasures. Although protecting data transmitted over the system is critical, previous work has not shown how to model these threats and countermeasures to evaluate attack impacts in each threat category. We propose a framework to evaluate the attack impact on data flows in systems with heterogeneous resources by representing the threats existing in each node and the countermeasures applied to data flows in their respective categories. Our framework determines whether a dataflow is compromised or not for each threat category. We define a hierarchical model of resources and vulnerabilities, represent threats and countermeasures by vectors, and develop a metric to quantify attack impacts. To validate the framework, we assess a simple IoT sensor system combining ZigBee and LoRa, demonstrating how it captures protocol and device differences. As a result, our framework flags only threats with realistic attack risks as compromised.

External IDs:dblp:conf/compsac/ShimodaKO25