학술논문

Anomaly Behavior Analysis of Smart Water Treatment Facility Service: Design, Analysis, and Evaluation
Document Type
Conference
Source
2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA) Computer Systems and Applications (AICCSA), 2023 20th ACS/IEEE International Conference on. :1-7 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Machine learning algorithms
Smart cities
Water quality
Sensor systems
Critical infrastructure
Water resources
Intelligent sensors
Drinking water treatment
machine learning
anomaly detection
cyber-physical system
cybersecurity
Language
ISSN
2161-5330
Abstract
The current trends toward the design and deployment of smart city services, including water services, improve quality, reliability and reduce operational costs. These advancements have led to the proliferation of ubiquitous connectivity to critical infrastructures. However, although smart sensors and Industrial Internet of Things (IIoTs) expedites rigorous monitoring and control, they exponentially increase vulnerabilities that can be exploited by cyberattacks. Therefore, development of advanced cybersecurity tools and resilience methods for smart city services are critically important because compromising these services can lead to disasters, accidents or even loss of life. To address the cybersecurity challenges facing smart city services, researchers need realistic testbeds to perform experiments, collect real-time data, and evaluate different security algorithms to protect smart critical infrastructure services. This paper presents a Water Treatment Facility Testbed (WTFT), a Cyber-Physical System (CPS) developed to enable experimentation with cybersecurity and resilient algorithms to deliver smart water services that can tolerate cyberattacks. Furthermore, an anomaly-based detection unit for water quality is implemented and our experimental results show a 96.8% F1-score, and a 98.3% accuracy with an attack detection latency under two seconds.