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National Science Foundation

Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

CPS-VO

real-world insider threat data

biblio

Visible to the public Anomaly Detection with Graph Convolutional Networks for Insider Threat and Fraud Detection

Submitted by grigby1 on Fri, 06/26/2020 - 1:04pm
  • graph theory
  • security of data
  • security
  • Scalability
  • Resiliency
  • real-world insider threat data
  • pubcrawl
  • Organizations
  • Metrics
  • malicious threat groups
  • machine learning
  • learning (artificial intelligence)
  • Insider Threat Detection
  • Image edge detection
  • Anomaly Detection
  • graph convolutional networks
  • GCN
  • fraud detection
  • fraud
  • feature extraction
  • edge detection
  • Data models
  • convolutional neural nets
  • composability
  • associated threat groups
  • anomaly detection model
  • anomaly detection applications

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