Preliminary Architecture and a Pilot Implementation for a Malicious Emails Detection Solution-Reference-Cited by-同舟云学术

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Preliminary Architecture and a Pilot Implementation for a Malicious Emails Detection Solution

Published:2023-06-29 Issue: Volume: Page:
ISSN:
Container-title:2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)
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Author:

Stalidi Cosmina¹,Popovici Eduard-Cristian²,Suciu George¹

Affiliation:

1. POLITEHNICA University of Bucharest, BEIA Consult International,Faculty of Electronics, Telecommunications, and Information Technology,Telecommunications Dept., R&D Department,Bucharest,Romania

2. POLITEHNICA University of Bucharest Project Manager MICRO ART CONSULT SRL,Faculty of Electronics, Telecommunications, and Information Technology,Telecommunications Dept.,Bucharest,Romania

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10193876/10193857/10193949.pdf?arnumber=10193949

Reference16 articles.

1. Scalable graph learning for anti-money /aundering: Afirst look;weber;ArXiv,2018

2. How powerful are graph neural networks;xu;International Conference on Learning Representations,0

3. Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

4. Evolvegcn: Evolving graph convolutional networks for dynamic graphs;pareja;ArXiv,2019

5. Computational Capabilities of Graph Neural Networks

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