Anomaly Detection in Smart Environments: A Comprehensive Survey
Anomaly detection is a critical task in ensuring the security and safety of infrastructure and
individuals in smart environments. This paper provides a comprehensive analysis of recent …
individuals in smart environments. This paper provides a comprehensive analysis of recent …
A review of deep learning based anomaly detection strategies in Industry 4.0 focused on application fields, sensing equipment and algorithms
Anomaly detection is a topic of interest in several areas, ranging from Industry 4.0 to Energy
Management, Smart Agriculture, Cybersecurity, and Bioinformatics. In a wide sense …
Management, Smart Agriculture, Cybersecurity, and Bioinformatics. In a wide sense …
False data injection attack detection in smart grid using energy consumption forecasting
Supervisory Control and Data Acquisition (SCADA) systems are essential for reliable
communication and control of smart grids. However, in the cyber-physical realm, it becomes …
communication and control of smart grids. However, in the cyber-physical realm, it becomes …
Can industrial intrusion detection be simple?
Cyberattacks against industrial control systems pose a serious risk to the safety of humans
and the environment. Industrial intrusion detection systems oppose this threat by …
and the environment. Industrial intrusion detection systems oppose this threat by …
Anomaly Detection in Liquid Sodium Cold Trap Operation with Multisensory Data Fusion Using Long Short-Term Memory Autoencoder
Sodium-cooled fast reactors (SFR), which use high temperature fluid near ambient pressure
as coolant, are one of the most promising types of GEN IV reactors. One of the unique …
as coolant, are one of the most promising types of GEN IV reactors. One of the unique …
A Lightweight Unsupervised Intrusion Detection Model Based on Variational Auto-Encoder
Y Ren, K Feng, F Hu, L Chen, Y Chen - Sensors, 2023 - mdpi.com
With the gradual integration of internet technology and the industrial control field, industrial
control systems (ICSs) have begun to access public networks on a large scale. Attackers use …
control systems (ICSs) have begun to access public networks on a large scale. Attackers use …
A causality-inspired approach for anomaly detection in a water treatment testbed
Critical infrastructure, such as water treatment facilities, largely relies on the effective
functioning of industrial control systems (ICSs). Due to the wide adoption of high-speed …
functioning of industrial control systems (ICSs). Due to the wide adoption of high-speed …
NDAMA: A novel deep autoencoder and multivariate analysis approach for IOT-based methane gas leakage detection
K Dashdondov, MH Kim, K Jo - IEEE Access, 2023 - ieeexplore.ieee.org
Natural gas is widely used for domestic and industrial purposes, and whether it is being
leaked into the air cannot be directly known. The current problem is that gas leakage is not …
leaked into the air cannot be directly known. The current problem is that gas leakage is not …
Separable contextual graph neural networks to identify tailgating-oriented traffic congestion
J Lee, S Lee - Expert Systems with Applications, 2024 - Elsevier
Identifying largescale traffic congestion with thousands of robots is a complicated task
involving structured-data graphical modeling, and it has recently gained more research …
involving structured-data graphical modeling, and it has recently gained more research …
A Variational Autoencoder Framework for Robust, Physics-Informed Cyberattack Recognition in Industrial Cyber-Physical Systems
Cybersecurity of Industrial Cyber-Physical Systems is drawing significant concerns as data
communication increasingly leverages wireless networks. A lot of data-driven methods were …
communication increasingly leverages wireless networks. A lot of data-driven methods were …