A hybrid model for building energy consumption forecasting using long short term memory networks
Data driven building energy consumption forecasting models play a significant role in
enhancing the energy efficiency of the buildings through building energy management …
enhancing the energy efficiency of the buildings through building energy management …
Hybrid approach to intrusion detection in fog-based IoT environments
CA De Souza, CB Westphall, RB Machado… - Computer Networks, 2020 - Elsevier
Abstract In the Internet of Things (IoT) systems, information of various kinds is continuously
captured, processed, and transmitted by systems generally interconnected by the Internet …
captured, processed, and transmitted by systems generally interconnected by the Internet …
FCM–SVM based intrusion detection system for cloud computing environment
Cloud computing offer various services over the Internet based on pay-per-use concept.
Therefore, many organizations have already adopted this system to attract the users with its …
Therefore, many organizations have already adopted this system to attract the users with its …
A multilayer perceptron model for anomaly detection in water treatment plants
Early and accurate anomaly detection in critical infrastructure (CI), such as water treatment
plants and electric power grid, is necessary to avoid plant damage and service disruption …
plants and electric power grid, is necessary to avoid plant damage and service disruption …
An efficient intrusion detection technique based on support vector machine and improved binary gravitational search algorithm
MR Gauthama Raman, N Somu, S Jagarapu… - Artificial Intelligence …, 2020 - Springer
Abstract 'Curse of Dimensionality'and the trade-off between high detection rate and less
false alarm rate make the design of an efficient and robust Intrusion Detection System, an …
false alarm rate make the design of an efficient and robust Intrusion Detection System, an …
A novel network intrusion detection system based on CNN
L Chen, X Kuang, A Xu, S Suo… - 2020 eighth international …, 2020 - ieeexplore.ieee.org
Network intrusion detection system (NIDS) plays an important role in network security. It can
detect the malicious traffic and prevent the network intrusion. Traditional methods used …
detect the malicious traffic and prevent the network intrusion. Traditional methods used …
Detection of cyberattacks in industrial control systems using enhanced principal component analysis and hypergraph-based convolution neural network (EPCA-HG …
K Krithivasan, S Pravinraj, SS VS - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The automated operations of industrial control systems (ICSs) highly rely on the
interconnected devices, sensors, and actuators that are monitored and controlled by the …
interconnected devices, sensors, and actuators that are monitored and controlled by the …
Challenges in machine learning based approaches for real-time anomaly detection in industrial control systems
Data-centric approaches are becoming increasingly common in the creation of defense
mechanisms for critical infrastructure such as the electric power grid and water treatment …
mechanisms for critical infrastructure such as the electric power grid and water treatment …
Generative adversarial attacks against intrusion detection systems using active learning
Intrusion Detection Systems (IDS) are increasingly adopting machine learning (ML)-based
approaches to detect threats in computer networks due to their ability to learn underlying …
approaches to detect threats in computer networks due to their ability to learn underlying …
Deep autoencoders as anomaly detectors: Method and case study in a distributed water treatment plant
Abstract Industrial Control Systems (ICS) are found in critical infrastructure, such as, water
treatment plants and oil refineries. ICS are often the target of cyber-attacks leading to …
treatment plants and oil refineries. ICS are often the target of cyber-attacks leading to …