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Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines
As industries become automated and connectivity technologies advance, a wide range of
systems continues to generate massive amounts of data. Many approaches have been …
systems continues to generate massive amounts of data. Many approaches have been …
Deep learning for time series anomaly detection: A survey
Time series anomaly detection is important for a wide range of research fields and
applications, including financial markets, economics, earth sciences, manufacturing, and …
applications, including financial markets, economics, earth sciences, manufacturing, and …
Attack graph model for cyber-physical power systems using hybrid deep learning
Electrical power grids are vulnerable to cyber attacks, as seen in Ukraine in 2015 and 2016.
However, existing attack detection methods are limited. Most of them are based on power …
However, existing attack detection methods are limited. Most of them are based on power …
Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study
In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …
detection, the datasets used, and a comparative study. Specifically, we provide a review of …
Deep learning for anomaly detection: A survey
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
Machine learning driven smart electric power systems: Current trends and new perspectives
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
Security of wide-area monitoring, protection, and control (WAMPAC) systems of the smart grid: A survey on challenges and opportunities
The evolution of power generation systems, along with their related increase in complexity,
led to the critical necessity of Wide-Area Monitoring, Protection, and Control (WAMPAC) …
led to the critical necessity of Wide-Area Monitoring, Protection, and Control (WAMPAC) …
Deep learning-based anomaly detection in cyber-physical systems: Progress and opportunities
Anomaly detection is crucial to ensure the security of cyber-physical systems (CPS).
However, due to the increasing complexity of CPSs and more sophisticated attacks …
However, due to the increasing complexity of CPSs and more sophisticated attacks …
DeepCoin: A novel deep learning and blockchain-based energy exchange framework for smart grids
In this paper, we propose a novel deep learning and blockchain-based energy framework
for smart grids, entitled DeepCoin. The DeepCoin framework uses two schemes, a …
for smart grids, entitled DeepCoin. The DeepCoin framework uses two schemes, a …
Detection of real-time malicious intrusions and attacks in IoT empowered cybersecurity infrastructures
Computer viruses, malicious, and other hostile attacks can affect a computer network.
Intrusion detection is a key component of network security as an active defence technology …
Intrusion detection is a key component of network security as an active defence technology …