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April 22, 2026Open Access

AI-Based Approaches For Network Anomaly Detection

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Authors

PAPutri Anggraini

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Overview

Explores AI techniques enhancing anomaly detection in networks, implying improved cybersecurity effectiveness.

Key Points

  • The aim is to investigate AI-based techniques for detecting anomalies in network behavior to enhance cybersecurity.
  • Explored various AI models including supervised, unsupervised, and semi-supervised learning.
  • Implemented techniques like neural networks, clustering algorithms, and autoencoders for pattern recognition.
  • Highlighted real-time data processing and big data analytics for improved detection accuracy.
  • AI-based methods significantly increased the efficiency and adaptability of anomaly detection systems.
  • Identified challenges such as high false positive rates and proposed solutions like hybrid models.
  • Demonstrated effectiveness in sectors like healthcare and finance, showing the versatility of AI applications.

Cite This Study

Putri Anggraini (2024) studied this question.

synapsesocial.com/papers/69e8661d6e0dea528ddea811https://doi.org/10.5281/zenodo.19666655
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