Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
Surveying trust-based collaborative intrusion detection: state-of-the-art, challenges and future directions
Owing to the swift growth in cyber attacks, intrusion detection systems (IDSs) have become a
necessity to help safeguard personal and organizational assets. However, with the …
necessity to help safeguard personal and organizational assets. However, with the …
Imbalanced data classification: A KNN and generative adversarial networks-based hybrid approach for intrusion detection
With the continuous emergence of various network attacks, it is becoming more and more
important to ensure the security of the network. Intrusion detection, as one of the important …
important to ensure the security of the network. Intrusion detection, as one of the important …
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 …
to safeguard the integrity and availability of sensitive assets in the protected systems …
Multi-dimensional feature fusion and stacking ensemble mechanism for network intrusion detection
A robust network intrusion detection system (NIDS) plays an important role in cyberspace
security for protecting confidential systems from potential threats. In real world network, there …
security for protecting confidential systems from potential threats. In real world network, there …
A feature selection based on the farmland fertility algorithm for improved intrusion detection systems
TS Naseri, FS Gharehchopogh - Journal of Network and Systems …, 2022 - Springer
The development and expansion of the Internet and cyberspace have increased computer
systems attacks; therefore, Intrusion Detection Systems (IDSs) are needed more than ever …
systems attacks; therefore, Intrusion Detection Systems (IDSs) are needed more than ever …
A distributed ensemble design based intrusion detection system using fog computing to protect the internet of things networks
With the development of internet of things (IoT), capabilities of computing, networking
infrastructure, storage of data and management have come very close to the edge of …
infrastructure, storage of data and management have come very close to the edge of …
An integrated rule based intrusion detection system: analysis on UNSW-NB15 data set and the real time online dataset
Intrusion detection system (IDS) has been developed to protect the resources in the network
from different types of threats. Existing IDS methods can be classified as either anomaly …
from different types of threats. Existing IDS methods can be classified as either anomaly …
Effective feature extraction via stacked sparse autoencoder to improve intrusion detection system
B Yan, G Han - IEEE Access, 2018 - ieeexplore.ieee.org
Classification features are crucial for an intrusion detection system (IDS), and the detection
performance of IDS will change dramatically when providing different input features …
performance of IDS will change dramatically when providing different input features …
[HTML][HTML] Ensuring network security with a robust intrusion detection system using ensemble-based machine learning
MA Hossain, MS Islam - Array, 2023 - Elsevier
Intrusion detection is a critical aspect of network security to protect computer systems from
unauthorized access and attacks. The capacity of traditional intrusion detection systems …
unauthorized access and attacks. The capacity of traditional intrusion detection systems …