[HTML][HTML] A systematic literature review on cyber threat intelligence for organizational cybersecurity resilience

S Saeed, SA Suayyid, MS Al-Ghamdi, H Al-Muhaisen… - Sensors, 2023 - mdpi.com
Cybersecurity is a significant concern for businesses worldwide, as cybercriminals target
business data and system resources. Cyber threat intelligence (CTI) enhances …

[HTML][HTML] Agriculture 4.0 and beyond: Evaluating cyber threat intelligence sources and techniques in smart farming ecosystems

HT Bui, H Aboutorab, A Mahboubi, Y Gao… - Computers & …, 2024 - Elsevier
The digitisation of agriculture, integral to Agriculture 4.0, has brought significant benefits
while simultaneously escalating cybersecurity risks. With the rapid adoption of smart farming …

[HTML][HTML] Recursive feature elimination with cross-validation with decision tree: Feature selection method for machine learning-based intrusion detection systems

M Awad, S Fraihat - Journal of Sensor and Actuator Networks, 2023 - mdpi.com
The frequency of cyber-attacks on the Internet of Things (IoT) networks has significantly
increased in recent years. Anomaly-based network intrusion detection systems (NIDSs) offer …

MalBoT-DRL: Malware botnet detection using deep reinforcement learning in IoT networks

M Al-Fawa'reh, J Abu-Khalaf… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
In the dynamic landscape of cyber threats, multistage malware botnets have surfaced as
significant threats of concern. These sophisticated threats can exploit Internet of Things (IoT) …

A cloud intrusion detection systems based on dnn using backpropagation and pso on the cse-cic-ids2018 dataset

S Alzughaibi, S El Khediri - Applied Sciences, 2023 - mdpi.com
Cloud computing (CC) is becoming an essential technology worldwide. This approach
represents a revolution in data storage and collaborative services. Nevertheless, security …

[HTML][HTML] Deep autoencoder-based integrated model for anomaly detection and efficient feature extraction in IoT networks

KA Alaghbari, HS Lim, MHM Saad, YS Yong - IoT, 2023 - mdpi.com
The intrusion detection system (IDS) is a promising technology for ensuring security against
cyber-attacks in internet-of-things networks. In conventional IDS, anomaly detection and …

[HTML][HTML] Capturing low-rate DDoS attack based on MQTT protocol in software Defined-IoT environment

M Al-Fayoumi, QA Al-Haija - Array, 2023 - Elsevier
Abstract The MQTT (Message Queue Telemetry Transport) protocol has recently been
standardized to provide a lightweight open messaging service over low-bandwidth and …

[HTML][HTML] Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm

A John, IFB Isnin, SHH Madni, FB Muchtar - Intelligent Systems with …, 2024 - Elsevier
The intrusion detection system (IDS) model, which can identify the presence of intruders in
the network and take some predefined action for safe data transit across the network, is …

A deep learning approach for intrusion detection systems in cloud computing environments

WH Aljuaid, SS Alshamrani - Applied Sciences, 2024 - mdpi.com
Cloud computing services have become indispensable to people's lives. Many of their
activities are performed through cloud services, from small companies to large enterprises …

Timely detection of DDoS attacks in IoT with dimensionality reduction

P Kumari, AK Jain - Cluster Computing, 2024 - Springer
The exponential growth of IoT devices and their interdependency makes the technology
more vulnerable to network attacks like Distributed Denial of Service (DDoS) that interrupt …