Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques

Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques

The increasing relevance of anomaly detection in attributed networks is gaining traction in fields such as cybersecurity, finance, and healthcare. However, large-scale attributed networks often exhibit noisy and inconsistent node properties, which negatively affect anomaly detection accuracy and dis...

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Bibliographic Details
Main Authors: Wasim Khan, Mohammad Ishrat, Mohammad Nadeem Ahmed, Shafiqul Abidin, Mohammad Husain, Mohd Izhar, Abu Taha Zamani, Mohammad Rashid Hussain, Arshad Ali
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Anomaly detection
proximity preservation
self-supervised learning
Laplacian smoothing
Laplacian sharpening
generational adversarial network
Online Access:https://ieeexplore.ieee.org/document/10898008/
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https://ieeexplore.ieee.org/document/10898008/

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