A survey of CNN-based network intrusion detection
Over the past few years, Internet applications have become more advanced and widely
used. This has increased the need for Internet networks to be secured. Intrusion detection …
used. This has increased the need for Internet networks to be secured. Intrusion detection …
Advancing network security in industrial IoT: a deep dive into AI-enabled intrusion detection systems
The increasing use of Industrial Internet of Things (IIoT) devices has heightened concerns
about cybersecurity threats, particularly botnet attacks. Traditional internet communication …
about cybersecurity threats, particularly botnet attacks. Traditional internet communication …
Variational few-shot learning for microservice-oriented intrusion detection in distributed industrial IoT
Along with the popularity of the Internet of Things (IoT) techniques with several
computational paradigms, such as cloud and edge computing, microservice has been …
computational paradigms, such as cloud and edge computing, microservice has been …
[HTML][HTML] A stacking ensemble of deep learning models for IoT intrusion detection
The number of Internet of Things (IoT) devices has increased considerably in the past few
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …
DL‐IDS: Extracting Features Using CNN‐LSTM Hybrid Network for Intrusion Detection System
P Sun, P Liu, Q Li, C Liu, X Lu, R Hao… - Security and …, 2020 - Wiley Online Library
Many studies utilized machine learning schemes to improve network intrusion detection
systems recently. Most of the research is based on manually extracted features, but this …
systems recently. Most of the research is based on manually extracted features, but this …
STL-HDL: A new hybrid network intrusion detection system for imbalanced dataset on big data environment
The ability to process large amounts of data in real time using big data analytics tools brings
many advantages that can be used in intrusion detection systems. Deep learning …
many advantages that can be used in intrusion detection systems. Deep learning …
Intelligent techniques for detecting network attacks: review and research directions
The significant growth in the use of the Internet and the rapid development of network
technologies are associated with an increased risk of network attacks. Network attacks refer …
technologies are associated with an increased risk of network attacks. Network attacks refer …
Intrusion detection based on bidirectional long short-term memory with attention mechanism
With the recent developments in the Internet of Things (IoT), the amount of data collected
has expanded tremendously, resulting in a higher demand for data storage, computational …
has expanded tremendously, resulting in a higher demand for data storage, computational …
A novel multi-stage approach for hierarchical intrusion detection
An intrusion detection system (IDS), traditionally an example of an effective security
monitoring system, is facing significant challenges due to the ongoing digitization of our …
monitoring system, is facing significant challenges due to the ongoing digitization of our …
A novel network intrusion detection method based on metaheuristic optimisation algorithms
The growing use of the Internet with its vulnerabilities has necessitated the adoption of
Intrusion Detection Systems (IDS) to assure security. IDSs are protective systems that detect …
Intrusion Detection Systems (IDS) to assure security. IDSs are protective systems that detect …