Neural Network Model for Anomaly Detection in Cyber Security Systems
Design, Implementation, and Analysis
DOI:
https://doi.org/10.37932/jarekom.v1i1.905Keywords:
Model, Neural Network, Anomaly Detection, Cyber Security System, Implementation, AnalysisAbstract
The increase in complex and dynamic cyber attacks drives the need for artificial intelligence-based anomaly detection systems. This article develops a neural network model to detect anomalies in cyber security systems utilizing a Research and Development approach. The model is developed using deep learning approaches (Autoencoder and LSTM) and evaluated against real-world network traffic data. The results demonstrate high effectiveness in detecting intrusions in real-time. This model introduces a technology-based innovation with a positive impact on the national digital security landscape.
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