Characterizing Mobile Money Phishing Using Reinforcement Learning-Reference-Cited by-同舟云学术

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Characterizing Mobile Money Phishing Using Reinforcement Learning

Published:2023 Issue: Volume:11 Page:103839-103862
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Njoya Alima Nzeket¹^ORCID,Ngongag Vanelle Laure Tchaya²^ORCID,Tchakounté Franklin¹^ORCID,Atemkeng Marcellin³^ORCID,Fachkha Claude⁴^ORCID

Affiliation:

1. Department of Mathematics and Computer Science, Faculty of Science, University of Ngaoundéré, Ngaoundere, Cameroon

2. Department of SFTI, School of Chemical Engineering and Mineral Industries, University of Ngaoundéré, Ngaoundere, Cameroon

3. Department of Mathematics, Rhodes University, Grahamstown, South Africa

4. College of Engineering and IT, University of Dubai, Dubai, United Arab Emirates

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10256102.pdf?arnumber=10256102

Reference58 articles.

1. Classifying Swahili Smishing Attacks for Mobile Money Users: A Machine-Learning Approach

2. Detection of online phishing email using dynamic evolving neural network based on reinforcement learning

3. Control of fraud on mobile money services in Ghana: an exploratory study

4. A New Q-Learning Algorithm Based on the Metropolis Criterion

5. S-Detector: an enhanced security model for detecting Smishing attack for mobile computing

Cited by 1 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

1. Optimization of a Cluster-Based Energy Management System Using Deep Reinforcement Learning Without Affecting Prosumer Comfort: V2X Technologies and Peer-to-Peer Energy Trading;IEEE Access;2024

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