Performance Metrics of an Intrusion Detection System Through Window-Based Deep Learning Models

Journal Title: Journal of Data Science and Intelligent Systems - Year 2024, Vol 2, Issue 3

Abstract

Intrusion and prevention technologies perform reliably in harsh conditions by fortifying many of the world's highest security sites with few defects in high performance. This paper aims to contribute by designing an intrusion/preventive system using a window-based convolutional neural network (CNN), an integrated recurrent neural network (RNN), and autoencoders (AutoE) to detect and test the performance of the intrusion detection system. The data packets were converted to images where the pixels were used as input. The CNN architecture shows a three-layer model with high predictive performance. The result shows high performance on CNN as compared to both RNN and AutoE; CNN seems to resist overfitting more than the rest of the models. The future perspective would be to test the model on other standard methods such as support vector machine (SVM) and dynamic control systems.

Authors and Affiliations

Fatima Isiaka

Keywords

Related Articles

The Evolving Landscape of Oil and Gas Chemicals: Convergence of Artificial Intelligence and Chemical-Enhanced Oil Recovery in the Energy Transition Toward Sustainable Energy Systems and Net-Zero Emissions

Chemical-enhanced oil recovery (EOR) is a field of study that can gain significantly from artificial intelligence (AI), addressing uncertainties such as mobility control, interfacial tension reduction, wettability altera...

Random Forest Ensemble Machine Learning Model for Early Detection and Prediction of Weight Category

The number of insurgents in our nation today is significantly rising each day, and the majority of those affected are living as internally displaced persons (IDP) in various IDP camps. These people experience a variety o...

Applications of Quantum Computing in Health Sector

The purpose of this paper is to provide an overview of the current state of quantum computing in the health sector and to explore its potential future applications. Quantum computing has the potential to revolutionize a...

Intra-annual National Statistical Accounts Based on Machine Learning Algorithm

The methods used for forecasting financial series are based on the concept that a pattern can be identified in the data and distinguished from randomness by smoothing past values. This smoothing process eliminates random...

Voice Biomarkers for Parkinson's Disease Prediction Using Machine Learning Models with Improved Feature Reduction Techniques

As a chronic and life-threatening disease, Parkinson’s disease (PD) causes people to become rigid and inactive and have shaky voices. There is an argument that current PD detection techniques are ineffective due to their...

Download PDF file
  • EP ID EP752189
  • DOI -
  • Views 28
  • Downloads 0

How To Cite

Fatima Isiaka (2024). Performance Metrics of an Intrusion Detection System Through Window-Based Deep Learning Models. Journal of Data Science and Intelligent Systems, 2(3), -. https://europub.co.uk/articles/-A-752189