Author: Mahmoud Ghorbel

Mahmoud Ghorbel
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Mahmoud is a PhD researcher in machine learning. He also holds a bachelor's degree in physical science and a master's degree in telecommunications and networking systems. His current areas of research concern computer vision, stock market prediction and deep learning. He produced several scientific articles about person re- identification and the study of the robustness and stability of deep networks.

Beyond Passwords: A Multimodal Approach to Biometric Authentication Using ECG and Iris Data

AI Paper Summary
Biometric authentication has emerged as a promising solution to enhance security by offering a more robust defense against cyber threats. However, hackers can increasingly...

Frequency-Selective Adversarial Attack Against Deep Learning-Based Wireless Signal Classifiers

AI Paper Summary
Wireless communication is the foundation of modern systems, enabling critical applications in military, commercial, and civilian domains. Its increasing prevalence has changed daily life...

Balancing Privacy and Robustness in NLP: A New Approach for Secure Prompt Learning in LLMs

AI Paper Summary
Recent advances in natural language processing (NLP), led by large-scale pre-trained models such as GPT-3 and BERT, have transformed text generation and sentiment analysis...

Adversarial Machine Learning in Wireless Communication Systems

AI Paper Summary
Machine learning (ML) has revolutionized wireless communication systems, enhancing applications like modulation recognition, resource allocation, and signal detection. However, the growing reliance on ML...

Synthetic Data Outliers: Navigating Identity Disclosure

AI Paper Summary
Synthetic data creation uses sophisticated algorithms like GANs, VAEs, or diffusion models to generate imitation datasets that mimic the statistical characteristics of real-world data....

This AI Paper Propsoes an AI Framework to Prevent Adversarial Attacks on Mobile Vehicle-to-Microgrid Services

AI Paper Summary
Mobile Vehicle-to-Microgrid (V2M) services enable electric vehicles to supply or store energy for localized power grids, enhancing grid stability and flexibility. AI is crucial...

Analysis of Deceptive Data Attacks with Adversarial Machine Learning for Solar Photovoltaic Power Generation Forecasting

AI Paper Summary
Photovoltaic energy, which uses solar panels to turn sunlight into electricity, is an important part of the shift to renewable energy. Deep learning-based prediction...

Exploring the Influence of Code Generation Tools (ChatGPT & GitHub Copilot) on Programming Education

AI Paper Summary
Integrating AI-powered code-generating technologies, such as ChatGPT and GitHub Copilot, is revolutionizing programming education. These tools, by providing real-time assistance to developers, accelerate the...

DP-Norm: A Novel AI Algorithm for Highly Privacy-Preserving Decentralized Federated Learning (FL)

AI Paper Summary
Federated Learning (FL) is a successful solution for decentralized model training that prioritizes data privacy, allowing several nodes to learn together without sharing data....

Dynamic Differential Privacy-based Dataset Condensation

AI Paper Summary
As the scale of data continues to expand, the need for efficient data condensation techniques has become increasingly important. Data condensation involves synthesizing a...

DPAdapter: A New Technique Designed to Amplify the Model Performance of Differentially Private Machine Learning DPML Algorithms by Enhancing Parameter Robustness

AI Shorts
Privacy in machine learning is critical, especially when models are trained on sensitive data. Differential privacy (DP) offers a framework to protect individual privacy...

FlexEval: An Open-Source AI Tool for Chatbot Performance Evaluation and Dialogue Analysis

AI Paper Summary
A Large Language Model (LLM) is an advanced type of artificial intelligence designed to understand and generate human-like text. It's trained on vast amounts...
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