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Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges
Anomaly detection has recently been applied to various areas, and several techniques
based on deep learning have been proposed for the analysis of multivariate time series. In …
based on deep learning have been proposed for the analysis of multivariate time series. In …
GAN-based anomaly detection: A review
Supervised learning algorithms have shown limited use in the field of anomaly detection due
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …
Smart grid cyber-physical situational awareness of complex operational technology attacks: A review
The smart grid (SG), regarded as the complex cyber-physical ecosystem of infrastructures,
orchestrates advanced communication, computation, and control technologies to interact …
orchestrates advanced communication, computation, and control technologies to interact …
An enhanced AI-based network intrusion detection system using generative adversarial networks
As communication technology advances, various and heterogeneous data are
communicated in distributed environments through network systems. Meanwhile, along with …
communicated in distributed environments through network systems. Meanwhile, along with …
A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Machine learning-based intrusion detection for smart grid computing: A survey
Machine learning (ML)-based intrusion detection system (IDS) approaches have been
significantly applied and advanced the state-of-the-art system security and defense …
significantly applied and advanced the state-of-the-art system security and defense …
Synthetic attack data generation model applying generative adversarial network for intrusion detection
Detecting a large number of attack classes accurately applying machine learning (ML) and
deep learning (DL) techniques depends on the number of representative samples available …
deep learning (DL) techniques depends on the number of representative samples available …
[HTML][HTML] Cyber threats to smart grids: Review, taxonomy, potential solutions, and future directions
Smart Grids (SGs) are governed by advanced computing, control technologies, and
networking infrastructure. However, compromised cybersecurity of the smart grid not only …
networking infrastructure. However, compromised cybersecurity of the smart grid not only …
[HTML][HTML] Proposed algorithm for smart grid DDoS detection based on deep learning
Abstract The Smart Grid's objective is to increase the electric grid's dependability, security,
and efficiency through extensive digital information and control technology deployment. As a …
and efficiency through extensive digital information and control technology deployment. As a …
Development of an end-to-end deep learning framework for sign language recognition, translation, and video generation
The recent developments in deep learning techniques evolved to new heights in various
domains and applications. The recognition, translation, and video generation of Sign …
domains and applications. The recognition, translation, and video generation of Sign …