Performance analysis of machine learning algorithms in intrusion detection system: A review

T Saranya, S Sridevi, C Deisy, TD Chung… - Procedia Computer …, 2020 - Elsevier
The rapid growth of technologies not only formulates life easier but also exposes a lot of
security issues. With the advancement of the Internet over years, the number of attacks over …

Machine learning and deep learning methods for intrusion detection systems: recent developments and challenges

G Kocher, G Kumar - Soft Computing, 2021 - Springer
Deep learning (DL) is gaining significant prevalence in every field of study due to its
domination in training large data sets. However, several applications are utilizing machine …

A hybrid intrusion detection model using ega-pso and improved random forest method

AK Balyan, S Ahuja, UK Lilhore, SK Sharma… - Sensors, 2022 - mdpi.com
Due to the rapid growth in IT technology, digital data have increased availability, creating
novel security threats that need immediate attention. An intrusion detection system (IDS) is …

Explainable artificial intelligence (XAI) to enhance trust management in intrusion detection systems using decision tree model

B Mahbooba, M Timilsina, R Sahal, M Serrano - Complexity, 2021 - Wiley Online Library
Despite the growing popularity of machine learning models in the cyber‐security
applications (eg, an intrusion detection system (IDS)), most of these models are perceived …

A novel PCA-firefly based XGBoost classification model for intrusion detection in networks using GPU

S Bhattacharya, PKR Maddikunta, R Kaluri, S Singh… - Electronics, 2020 - mdpi.com
The enormous popularity of the internet across all spheres of human life has introduced
various risks of malicious attacks in the network. The activities performed over the network …

Deep learning approach for SDN-enabled intrusion detection system in IoT networks

R Chaganti, W Suliman, V Ravi, A Dua - Information, 2023 - mdpi.com
Owing to the prevalence of the Internet of things (IoT) devices connected to the Internet, the
number of IoT-based attacks has been growing yearly. The existing solutions may not …

Intrusion detection technique in wireless sensor network using grid search random forest with Boruta feature selection algorithm

S Subbiah, KSM Anbananthen… - Journal of …, 2022 - ieeexplore.ieee.org
Attacks in wireless sensor networks (WSNs) aim to prevent or eradicate the network's ability
to perform its anticipated functions. Intrusion detection is a defense used in wireless sensor …

A convolutional neural network for improved anomaly-based network intrusion detection

I Al-Turaiki, N Altwaijry - Big Data, 2021 - liebertpub.com
Cybersecurity protects and recovers computer systems and networks from cyber attacks. The
importance of cybersecurity is growing commensurately with people's increasing reliance on …

An intrusion detection approach using ensemble support vector machine based chaos game optimization algorithm in big data platform

A Ponmalar, V Dhanakoti - Applied Soft Computing, 2022 - Elsevier
The mainstream computing technology is not efficient in managing massive data and
detecting network traffic intrusions, often including big data. The intrusions present in …

A generalized machine learning model for DDoS attacks detection using hybrid feature selection and hyperparameter tuning

RK Batchu, H Seetha - Computer Networks, 2021 - Elsevier
In the digital era, the usage of network-connected devices is rapidly growing which leads to
an increase in cyberattacks. Among them, Distributed Denial of Service (DDoS) attacks are …