[HTML][HTML] Survey on intrusion detection systems based on machine learning techniques for the protection of critical infrastructure
A Pinto, LC Herrera, Y Donoso, JA Gutierrez - Sensors, 2023 - mdpi.com
Industrial control systems (ICSs), supervisory control and data acquisition (SCADA) systems,
and distributed control systems (DCSs) are fundamental components of critical infrastructure …
and distributed control systems (DCSs) are fundamental components of critical infrastructure …
X-IIoTID: A connectivity-agnostic and device-agnostic intrusion data set for industrial Internet of Things
M Al-Hawawreh, E Sitnikova… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) is a high-value cyber target due to the nature of the
devices and connectivity protocols they deploy. They are easy to compromise and, as they …
devices and connectivity protocols they deploy. They are easy to compromise and, as they …
Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach
The constantly evolving digital transformation imposes new requirements on our society.
Aspects relating to reliance on the networking domain and the difficulty of achieving security …
Aspects relating to reliance on the networking domain and the difficulty of achieving security …
Datasets are not enough: Challenges in labeling network traffic
In contrast to previous surveys, the present work is not focused on reviewing the datasets
used in the network security field. The fact is that many of the available public labeled …
used in the network security field. The fact is that many of the available public labeled …
A critical review of common log data sets used for evaluation of sequence-based anomaly detection techniques
Log data store event execution patterns that correspond to underlying workflows of systems
or applications. While most logs are informative, log data also include artifacts that indicate …
or applications. While most logs are informative, log data also include artifacts that indicate …
[HTML][HTML] Generating network intrusion detection dataset based on real and encrypted synthetic attack traffic
A Ferriyan, AH Thamrin, K Takeda, J Murai - applied sciences, 2021 - mdpi.com
The lack of publicly available up-to-date datasets contributes to the difficulty in evaluating
intrusion detection systems. This paper introduces HIKARI-2021, a dataset that contains …
intrusion detection systems. This paper introduces HIKARI-2021, a dataset that contains …
Transferability of machine learning models learned from public intrusion detection datasets: the CICIDS2017 case study
Intrusion detection is a primary concern in any modern computer system due to the ever-
growing number of intrusions. Machine learning represents an effective solution to detect …
growing number of intrusions. Machine learning represents an effective solution to detect …
[HTML][HTML] On the improvement of the isolation forest algorithm for outlier detection with streaming data
In recent years, detecting anomalies in real-world computer networks has become a more
and more challenging task due to the steady increase of high-volume, high-speed and high …
and more challenging task due to the steady increase of high-volume, high-speed and high …
Netdiffusion: Network data augmentation through protocol-constrained traffic generation
Datasets of labeled network traces are essential for a multitude of machine learning (ML)
tasks in networking, yet their availability is hindered by privacy and maintenance concerns …
tasks in networking, yet their availability is hindered by privacy and maintenance concerns …
FedChain-Hunter: A reliable and privacy-preserving aggregation for federated threat hunting framework in SDN-based IIoT
In the development of the Industrial Internet of Things (IIoT), cyber threats and attacks have
become major issues and concerns in Industry 4.0 due to the negative impacts on the …
become major issues and concerns in Industry 4.0 due to the negative impacts on the …