Machine learning for anomaly detection: A systematic review

AB Nassif, MA Talib, Q Nasir, FM Dakalbab - Ieee Access, 2021 - ieeexplore.ieee.org
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

Machine learning towards intelligent systems: applications, challenges, and opportunities

MN Injadat, A Moubayed, AB Nassif… - Artificial Intelligence …, 2021 - Springer
The emergence and continued reliance on the Internet and related technologies has
resulted in the generation of large amounts of data that can be made available for analyses …

Machine learning methods for cyber security intrusion detection: Datasets and comparative study

IF Kilincer, F Ertam, A Sengur - Computer Networks, 2021 - Elsevier
The increase in internet usage brings security problems with it. Malicious software can affect
the operation of the systems and disrupt data confidentiality due to the security gaps in the …

MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles

L Yang, A Moubayed, A Shami - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …

Multi-stage optimized machine learning framework for network intrusion detection

MN Injadat, A Moubayed, AB Nassif… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …

Near real-time wind speed forecast model with bidirectional LSTM networks

LP Joseph, RC Deo, R Prasad, S Salcedo-Sanz… - Renewable Energy, 2023 - Elsevier
Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …

Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture

LP Joseph, EA Joseph, R Prasad - Computers in Biology and Medicine, 2022 - Elsevier
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …

Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation

BA Tama, S Lim - Computer Science Review, 2021 - Elsevier
Intrusion detection systems (IDSs) are intrinsically linked to a comprehensive solution of
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …

Tree-based intelligent intrusion detection system in internet of vehicles

L Yang, A Moubayed, I Hamieh… - 2019 IEEE global …, 2019 - ieeexplore.ieee.org
The use of autonomous vehicles (AVs) is a promising technology in Intelligent
Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything …

IoT data analytics in dynamic environments: From an automated machine learning perspective

L Yang, A Shami - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
With the wide spread of sensors and smart devices in recent years, the data generation
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …