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Graph Anomaly Detection Based on Steiner Connectivity and Density

  • Published:2018-05 Issue:5 Volume:106 Page:829-845
  • ISSN:0018-9219
  • Container-title:Proceedings of the IEEE
  • language:
  • Short-container-title:Proc. IEEE

Author:

Cadena JoseORCID,Chen Feng,Vullikanti Anil

Funder

Defense Threat Reduction Agency (DTRA) Comprehensive National Incident Management System (CNIMS)

National Science Foundation (NSF)

NSF

Army Research Office (ARO)

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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3. Exploiting Spatial-Temporal Behavior Patterns for Fraud Detection in Telecom Networks;IEEE Transactions on Dependable and Secure Computing;2022

4. Integrating social influence modeling and user modeling for trust prediction in signed networks;Artificial Intelligence;2022-01

5. Improved detection of Facebook anomalies and abnormalities using graph-based and machine learning techniques;PROCEEDING OF THE 1ST INTERNATIONAL CONFERENCE ON ADVANCED RESEARCH IN PURE AND APPLIED SCIENCE (ICARPAS2021): Third Annual Conference of Al-Muthanna University/College of Science;2022
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