A systematic literature review for network intrusion detection system (IDS)

OH Abdulganiyu, T Ait Tchakoucht… - International Journal of …, 2023 - Springer
With the recent increase in internet usage, the number of important, sensitive, confidential
individual and corporate data passing through internet has increasingly grown. With gaps in …

Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system

MHL Louk, BA Tama - Expert Systems with Applications, 2023 - Elsevier
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …

CSE-IDS: Using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems

N Gupta, V Jindal, P Bedi - Computers & Security, 2022 - Elsevier
In recent times, Network-based Intrusion Detection Systems (NIDSs) have become very
popular for detecting intrusions in computer networks. Existing NIDSs can easily identify …

An optimized ensemble prediction model using AutoML based on soft voting classifier for network intrusion detection

MA Khan, N Iqbal, H Jamil, DH Kim - Journal of Network and Computer …, 2023 - Elsevier
Traditional ML based IDS cannot handle high-speed and ever-evolving attacks.
Furthermore, these traditional IDS face several common challenges, such as processing …

[HTML][HTML] IDS-INT: Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

F Ullah, S Ullah, G Srivastava, JCW Lin - Digital Communications and …, 2024 - Elsevier
A network intrusion detection system is critical for cyber security against illegitimate attacks.
In terms of feature perspectives, network traffic may include a variety of elements such as …

A long short-term memory (LSTM)-based distributed denial of service (DDoS) detection and defense system design in public cloud network environment

H Aydın, Z Orman, MA Aydın - Computers & Security, 2022 - Elsevier
The fact that cloud systems are under the increasing risks of cyber attacks has made the
phenomenon of information security first a need and then a necessity for these systems …

BoostedEnML: Efficient technique for detecting cyberattacks in IoT systems using boosted ensemble machine learning

OD Okey, SS Maidin, P Adasme, R Lopes Rosa… - Sensors, 2022 - mdpi.com
Following the recent advances in wireless communication leading to increased Internet of
Things (IoT) systems, many security threats are currently ravaging IoT systems, causing …

An innovative perceptual pigeon galvanized optimization (PPGO) based likelihood Naïve Bayes (LNB) classification approach for network intrusion detection system

S Shitharth, PR Kshirsagar, PK Balachandran… - IEEE …, 2022 - ieeexplore.ieee.org
Intrusion detection and classification have gained significant attention recently due to the
increased utilization of networks. For this purpose, there are different types of Network …

[HTML][HTML] Explainable prediction of loan default based on machine learning models

X Zhu, Q Chu, X Song, P Hu, L Peng - Data Science and Management, 2023 - Elsevier
Owing to the convenience of online loans, an increasing number of people are borrowing
money on online platforms. With the emergence of machine learning technology, predicting …

[HTML][HTML] A review on recent approaches of machine learning, deep learning, and explainable artificial intelligence in intrusion detection systems

SB Mallampati, S Hari - Majlesi Journal of Electrical Engineering, 2023 - journals.iau.ir
In recent decades, network security has become increasingly crucial, and intrusion detection
systems play a critical role in securing it. An intrusion Detection System (IDS) is a …