Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding

Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding

Attributed networks are prevalent in the current information infrastructure, where node attributes enhance knowledge discovery. Anomaly detection in attributed networks is gaining attention for its potential uses in cybersecurity, finance, and healthcare. Recognizing the complicated relationship bet...

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Bibliographic Details
Main Authors: Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Attributed networks anomaly detection
random masking and padding
correlation analysis
graph convolution network
KL divergence
deep learning
Online Access:https://ieeexplore.ieee.org/document/10522661/
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