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سميه سعد سليمان صديق - Sumaya Saad Sulaiman
MSc - assistant lecturer
College of Science , Department of Computer
[email protected]
Summary

Sumaya S. Sulaiman was born in Baghdad, Iraq in 1983. She received the B.Sc., M.Sc. and PhD. degrees in computer science from the University of Baghdad and University of Mustansiriyah, Iraq in 2005, 2013 and 2025 respectively. She is now a lecturer in the Department of Computer Science at the University of Baghdad. Sumaya S. sulaiman research areas mainly include computer and data security. She joins different committees at the College and Department levels.

Teaching materials
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CRYPTOGRAPHY
كلية العلوم
الحاسوب
Stage 3
Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Scopus (10)
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Publication Date
Thu Nov 19 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Enhanced Multistage RSA Encryption Model
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Credit Card Fraud Detection Challenges and Solutions: A Review
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     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c

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Scopus (11)
Crossref (10)
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Publication Date
Sat Aug 31 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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Publication Date
Mon Jun 30 2025
Journal Name
Iraqi Journal Of Science
New Weighted Synthetic Oversampling Method for Improving Credit Card Fraud Detection
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The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

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