Machine learning and deep learning methods for intrusion detection systems: A survey

H Liu, B Lang - applied sciences, 2019 - mdpi.com
Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …

A survey of crypto ransomware attack detection methodologies: an evolving outlook

A Alqahtani, FT Sheldon - Sensors, 2022 - mdpi.com
Recently, ransomware attacks have been among the major threats that target a wide range
of Internet and mobile users throughout the world, especially critical cyber physical systems …

Building an efficient intrusion detection system based on feature selection and ensemble classifier

Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …

Cyberattacks detection in iot-based smart city applications using machine learning techniques

MM Rashid, J Kamruzzaman, MM Hassan… - International Journal of …, 2020 - mdpi.com
In recent years, the widespread deployment of the Internet of Things (IoT) applications has
contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies …

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 …

On the performance of machine learning models for anomaly-based intelligent intrusion detection systems for the internet of things

G Abdelmoumin, DB Rawat… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Anomaly-based machine learning-enabled intrusion detection systems (AML-IDSs) show
low performance and prediction accuracy while detecting intrusions in the Internet of Things …

Data mining techniques in intrusion detection systems: A systematic literature review

F Salo, M Injadat, AB Nassif, A Shami, A Essex - IEEE Access, 2018 - ieeexplore.ieee.org
The continued ability to detect malicious network intrusions has become an exercise in
scalability, in which data mining techniques are playing an increasingly important role. We …

Ensemble detection model for IoT IDS

A Alhowaide, I Alsmadi, J Tang - Internet of Things, 2021 - Elsevier
The constant development of interrelated computing devices and the emergence of new
network technologies have dramatically increased the Internet of Things (IoT) devices …

Crypto-ransomware early detection model using novel incremental bagging with enhanced semi-random subspace selection

BAS Al-rimy, MA Maarof, SZM Shaid - Future Generation Computer Systems, 2019 - Elsevier
The irreversible effect is what characterizes crypto-ransomware and distinguishes it from
traditional malware. That is, even after neutralizing the attack, the targeted files remain …

RFAODE: A novel ensemble intrusion detection system

MA Jabbar, R Aluvalu - Procedia computer science, 2017 - Elsevier
In recent years information and communication technology (ICT) has become an important
part of human life. But ICT brings a lot of cyber risks. New threats and vulnerabilities are …