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Mohammed E.

@Erraghay

monthly-level-three.svg
5.0
1
1.4
1.4
100%

Full-Stack Developer | Cybersecurity Engineer

$10 USD / Hour
・
Flag of
Morocco (1:17 PM)
・
Joined on December 16, 2024
$10 USD / Hour
・
I am a Cybersecurity Expert and Full-Stack Developer with a comprehensive skill set in secure software development, network security, and user-centric design. My expertise includes building robust and secure web applications while ensuring an intuitive user experience and resilient system architecture. In the field of information security, I specialize in identifying vulnerabilities, implementing security controls, and fortifying applications against cyber threats. I have experience conducting penetration testing, securing networks, and integrating security best practices into every stage of development. My proficiency extends to Linux systems, scripting, and tools essential for safeguarding digital assets. As a full-stack developer, I am proficient in HTML, CSS, JavaScript, React, Node.js, and Python, delivering scalable and responsive web solutions. My attention to UI/UX design principles ensures that the applications I develop are not only secure but also visually appealing and user-friendly. If you're looking for a professional who can provide secure, functional, and beautifully designed applications, I am confident in delivering solutions tailored to your needs. Let’s collaborate to bring your ideas to life — with security, efficiency, and exceptional design at the forefront.
Verifications
On time
100%
On budget
100%
Accept rate
100%
Freelancer PHP Developers Morocco
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Portfolio

Portfolio

12416264
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
12416256
Developed a full-stack platform enabling gamer streamers to engage audiences in charitable donations. Implemented the backend using Django and Django REST Framework to manage user accounts, donations, and events. Created an interactive and responsive frontend with React.js. Designed an intuitive UI/UX in Figma, enhancing user experience. Integrated third-party APIs for real-time donation tracking, social media updates, and live event features. Deployed the platform on Heroku, ensuring scalability and optimized performance.
Charity-Oriented Full-Stack Gaming P
Developed a full-stack platform enabling gamer streamers to engage audiences in charitable donations. Implemented the backend using Django and Django REST Framework to manage user accounts, donations, and events. Created an interactive and responsive frontend with React.js. Designed an intuitive UI/UX in Figma, enhancing user experience. Integrated third-party APIs for real-time donation tracking, social media updates, and live event features. Deployed the platform on Heroku, ensuring scalability and optimized performance.
Charity-Oriented Full-Stack Gaming P
12416250
Area117. This advanced real-time peer-to-peer chat application leverages WebRTC to enable direct, secure communication between users, eliminating the need for central servers and significantly enhancing privacy. The core of Area117's design is its peer-to-peer architecture, which establishes direct encrypted data channels between users. This approach not only ensures that all communications remain confidential but also optimizes data transmission by bypassing intermediary servers. With end-to-end encryption via RSA, our system guarantees that messages and file transfers are protected against unauthorized access. Creating Area117 involved navigating sophisticated engineering challenges, such as ensuring the seamless performance of peer-to-peer connections and implementing cutting-edge cryptographic measures. This project has been a deep dive into the intricacies of secure, decentralized communication, enhancing our expertise in both real-time data transmission and advanced encryption
Peer-to-Peer Real-Time Chat-app
Area117. This advanced real-time peer-to-peer chat application leverages WebRTC to enable direct, secure communication between users, eliminating the need for central servers and significantly enhancing privacy. The core of Area117's design is its peer-to-peer architecture, which establishes direct encrypted data channels between users. This approach not only ensures that all communications remain confidential but also optimizes data transmission by bypassing intermediary servers. With end-to-end encryption via RSA, our system guarantees that messages and file transfers are protected against unauthorized access. Creating Area117 involved navigating sophisticated engineering challenges, such as ensuring the seamless performance of peer-to-peer connections and implementing cutting-edge cryptographic measures. This project has been a deep dive into the intricacies of secure, decentralized communication, enhancing our expertise in both real-time data transmission and advanced encryption
Peer-to-Peer Real-Time Chat-app
Area117. This advanced real-time peer-to-peer chat application leverages WebRTC to enable direct, secure communication between users, eliminating the need for central servers and significantly enhancing privacy. The core of Area117's design is its peer-to-peer architecture, which establishes direct encrypted data channels between users. This approach not only ensures that all communications remain confidential but also optimizes data transmission by bypassing intermediary servers. With end-to-end encryption via RSA, our system guarantees that messages and file transfers are protected against unauthorized access. Creating Area117 involved navigating sophisticated engineering challenges, such as ensuring the seamless performance of peer-to-peer connections and implementing cutting-edge cryptographic measures. This project has been a deep dive into the intricacies of secure, decentralized communication, enhancing our expertise in both real-time data transmission and advanced encryption
Peer-to-Peer Real-Time Chat-app
12416264
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
In this project, I developed a Machine Learning-based malware detection system to identify malicious executable files. After collecting a dataset of labeled files (malicious or benign), I extracted relevant features from EXE files using the PEfile tool. I then trained multiple classification models, including Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN), using cross-validation techniques to evaluate their performance. The model was assessed based on metrics such as accuracy, recall, and F1 score. Finally, I automated the malware detection process by developing a system capable of classifying new files in real-time, with an alert and decision-making mechanism when malicious files are detected.
Malware Detection using ML
12416256
Developed a full-stack platform enabling gamer streamers to engage audiences in charitable donations. Implemented the backend using Django and Django REST Framework to manage user accounts, donations, and events. Created an interactive and responsive frontend with React.js. Designed an intuitive UI/UX in Figma, enhancing user experience. Integrated third-party APIs for real-time donation tracking, social media updates, and live event features. Deployed the platform on Heroku, ensuring scalability and optimized performance.
Charity-Oriented Full-Stack Gaming P
Developed a full-stack platform enabling gamer streamers to engage audiences in charitable donations. Implemented the backend using Django and Django REST Framework to manage user accounts, donations, and events. Created an interactive and responsive frontend with React.js. Designed an intuitive UI/UX in Figma, enhancing user experience. Integrated third-party APIs for real-time donation tracking, social media updates, and live event features. Deployed the platform on Heroku, ensuring scalability and optimized performance.
Charity-Oriented Full-Stack Gaming P
12416250
Area117. This advanced real-time peer-to-peer chat application leverages WebRTC to enable direct, secure communication between users, eliminating the need for central servers and significantly enhancing privacy. The core of Area117's design is its peer-to-peer architecture, which establishes direct encrypted data channels between users. This approach not only ensures that all communications remain confidential but also optimizes data transmission by bypassing intermediary servers. With end-to-end encryption via RSA, our system guarantees that messages and file transfers are protected against unauthorized access. Creating Area117 involved navigating sophisticated engineering challenges, such as ensuring the seamless performance of peer-to-peer connections and implementing cutting-edge cryptographic measures. This project has been a deep dive into the intricacies of secure, decentralized communication, enhancing our expertise in both real-time data transmission and advanced encryption
Peer-to-Peer Real-Time Chat-app
Area117. This advanced real-time peer-to-peer chat application leverages WebRTC to enable direct, secure communication between users, eliminating the need for central servers and significantly enhancing privacy. The core of Area117's design is its peer-to-peer architecture, which establishes direct encrypted data channels between users. This approach not only ensures that all communications remain confidential but also optimizes data transmission by bypassing intermediary servers. With end-to-end encryption via RSA, our system guarantees that messages and file transfers are protected against unauthorized access. Creating Area117 involved navigating sophisticated engineering challenges, such as ensuring the seamless performance of peer-to-peer connections and implementing cutting-edge cryptographic measures. This project has been a deep dive into the intricacies of secure, decentralized communication, enhancing our expertise in both real-time data transmission and advanced encryption
Peer-to-Peer Real-Time Chat-app
Area117. This advanced real-time peer-to-peer chat application leverages WebRTC to enable direct, secure communication between users, eliminating the need for central servers and significantly enhancing privacy. The core of Area117's design is its peer-to-peer architecture, which establishes direct encrypted data channels between users. This approach not only ensures that all communications remain confidential but also optimizes data transmission by bypassing intermediary servers. With end-to-end encryption via RSA, our system guarantees that messages and file transfers are protected against unauthorized access. Creating Area117 involved navigating sophisticated engineering challenges, such as ensuring the seamless performance of peer-to-peer connections and implementing cutting-edge cryptographic measures. This project has been a deep dive into the intricacies of secure, decentralized communication, enhancing our expertise in both real-time data transmission and advanced encryption
Peer-to-Peer Real-Time Chat-app
Changes saved
5.0 · 1 Review
Reviews
User Avatar
Site Web à Finaliser pour Associations • $50 USD
he 's very goot at what he does, and he is reliable and creative, i would definetly recommend him/work with him again
Imane B.
@Imanebelkhammar
•
Flag of
Marrakech, Morocco
•
4 days ago
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Education
National Institute of Posts and Telecommunications
2021 - 2024
•
3 years
Cybersecurity Engineer
Flag of
Morocco
2021 - 2024
•
3 years
Mathematics, Physics and Engineering Science
2019 - 2021
•
2 years
Flag of
Morocco
2019 - 2021
•
2 years
Baccalaureate in Mathematical Sciences
2016 - 2019
•
3 years
Flag of
Morocco
2016 - 2019
•
3 years
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