Novel online network intrusion detection system for industrial IoT based on OI-SVDD and AS-ELM
The Industrial Internet of Things (IIoT) should be equipped with computational resources to
detect network intrusions, types of attacks, and update their models automatically in real …
detect network intrusions, types of attacks, and update their models automatically in real …
Network based intrusion detection using the UNSW-NB15 dataset
S Meftah, T Rachidi, N Assem - International Journal of …, 2019 - journal.uob.edu.bh
In this work, we apply a two stage anomaly-based network intrusion detection process using
the UNSW-NB15 dataset. We use Recursive Feature Elimination and Random Forests …
the UNSW-NB15 dataset. We use Recursive Feature Elimination and Random Forests …
Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem
Network intrusion detection problem is an ongoing challenging research area because of a
huge number of traffic volumes, extremely imbalanced data sets, multi-class of attacks …
huge number of traffic volumes, extremely imbalanced data sets, multi-class of attacks …
基于独热编码和卷积神经网络的异常检测
梁杰， 陈嘉豪， 张雪芹， 周悦， 林家骏 - 清华大学学报(自然科学版), 2019 - cqvip.com
目前基于深度学习的网络异常检测是入侵检测领域新的研究方向, 但是大部分研究都是利用数据
挖掘处理后的特征数据进行特征学习和分类. 该文利用UNSWNB15 作为主要研究数据集 …
挖掘处理后的特征数据进行特征学习和分类. 该文利用UNSWNB15 作为主要研究数据集 …
Outlier dirichlet mixture mechanism: Adversarial statistical learning for anomaly detection in the fog
Current anomaly detection systems (ADSs) apply statistical and machine learning
algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced …
algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced …
A privacy-conserving framework based intrusion detection method for detecting and recognizing malicious behaviours in cyber-physical power networks
Abstract Contemporary Smart Power Systems (SPNs) depend on Cyber-Physical Systems
(CPSs) to connect physical devices and control tools. Developing a robust privacy …
(CPSs) to connect physical devices and control tools. Developing a robust privacy …
[PDF][PDF] Deep-intrusion detection system with enhanced UNSW-NB15 dataset based on deep learning techniques
Growth in the number of devices and data has raised serious security concerns, that have
increased the importance of the development of advanced intrusion detection systems (IDS) …
increased the importance of the development of advanced intrusion detection systems (IDS) …
An enhanced anomaly detection in web traffic using a stack of classifier ensemble
A Web attack protection system is extremely essential in today's information age. Classifier
ensembles have been considered for anomaly-based intrusion detection in Web traffic …
ensembles have been considered for anomaly-based intrusion detection in Web traffic …
Effect of balancing data using synthetic data on the performance of machine learning classifiers for intrusion detection in computer networks
Attacks on computer networks have increased significantly in recent days, due in part to the
availability of sophisticated tools for launching such attacks as well as the thriving …
availability of sophisticated tools for launching such attacks as well as the thriving …
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 …