Rule Specification-based Misbehavior Detection for IoT-Embedded Cyber Physical Systems
Abstract
The problem we propose to solve is the vulnerability to infrastructure damage, service interruption, and revenue loss caused by malicious Internet of Things (IoT) devices embedded in a cyber physical system such as an unmanned air vehicle (UAV) system with heterogeneous UAVs as the IoT constituents, a smart grid system with head-ends (HEs), distribution access points/data aggregation points (DAPs), and subscriber energy meters (SEMs) as the IoT constituents, a smart building embedding sensors, actuators, and microchips for sensing and control, or a safety-critical medical system with vital sign monitor (VSM), patient controlled analgesia (PCA), and cardiac device (CD) as the IoT constituents. We aim to provide a solution to this problem by detecting misbehavior of embedded IoT devices that exploit the vulnerability through known or unknown attacks. The solution we are offering is a lightweight behavior rule specification-based monitoring technique with which misbehavior of an IoT device manifested as a result of attacks exploiting the vulnerability exposed may be detected through automatic model checking and formal verification, regardless of whether the attack is known or unknown. We aim to provide a solution for malicious IoT device detection that is accurate in detection rate (close to 100%) while limiting the false positive probability to a minimum (less than 3%). We aim to verify that our rule specification-based misbehavior detection technique can outperform contemporary anomaly-based misbehavior detection techniques through a comprehensive comparative analysis for real-world IoT-embedded applications described above.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 09, 2018
- Source ID
- FA23861714076
Entities
People
- Ing-Ray Chen
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- Virginia Tech