Team Members
![](https://cscgp.miuegypt.edu.eg/wp-content/uploads/2024/06/cropped-adham-kamal-abdelkhalek-mohamed-2021-06260-Adham-Adham-Kamal-Ali.jpg)
Adham Kamal
Team Leader
![](https://cscgp.miuegypt.edu.eg/wp-content/uploads/2024/06/cropped-yousef-hany-nasr-el-deen-khattab-2021-07006.jpeg-Adham-Adham-Kamal-Ali.jpg)
Yousef Hany
Team Member
![](https://cscgp.miuegypt.edu.eg/wp-content/uploads/2024/06/cropped-youssef-mohammed-elsaeed-mahgoub-2020-11170-Adham-Adham-Kamal-Ali.jpg)
Youssef Mohammed
Team Member
![](https://cscgp.miuegypt.edu.eg/wp-content/uploads/2024/06/cropped-omar-khaled-2020-12690-Adham-Adham-Kamal-Ali.jpg)
Omar Khaled
Team Member
Supervisors
![](https://cscgp.miuegypt.edu.eg/wp-content/uploads/2024/06/cropped-Nermin-Naguib-Nermin-Jean.jpg)
Dr. Nermin Naguib
Doctor
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Eng. Jamila Ali
Teaching Assistant
![](https://cscgp.miuegypt.edu.eg/wp-content/uploads/2024/06/cropped-Bassant-Kassem-Bassant-Kassem.png)
Eng. Bassant Kassem
Teaching Assistant
Abstract
Malware detection refers to a collection of techniques used to detect all types of malicious software that might harm the victim’s system. Ai powered machine learning enhances malware detection processes by analyzing large amount of data by identifying the behavior of a malware to detect it. AI can detect malware through its behavior and signature techniques. We aim to protect computers from malicious infection and to provide a reliable solution, helping users protect their systems from evolving malware threats. The primary feature of the system is to detect and remove malicious code using AI algorithms to prevent malware from causing damage to your computer. The user will be notified when the system detects a malware and it recommends an action to the user, and it alerts users about malicious links. If the malware signature doesn’t exist in the database, it will be added as a new signature to the database.
System Objectives
Malware detection using a signature and behavior approaches.
• Creating an AI model that detects known and unknown types of malwares.
• Creating an application that ensures fast and reliable protection against malicious infections.
• Creating an application that has additional features which prevent data loss and securing confidential files against unauthorized access.
• Creating an application that alerts the user about any suspicious websites that might cause a
severe damage.
System Scope
Our system detects malware in different types of files using signature-based detection by calculating the hash of selected file and then comparing it through VirusTotal API. The system will detect malware in exe files through its behavior from the memory dumb analysis using AI algorithms. The system will recommend an action for the user to take when a malicious file is detected whether to delete the file or quarantine the file. The system will also detect suspicious URL’s that might harm the user’s device by checking the URL through VirusTotal API. The system can encrypt selected files that contain confidential information and can also backup certain files that the user selects for future retrieval. The system can scan USB devices to detect malware.
Documents and Presentations
Proposal
You will find here the documents and presentation for our proposal.
SRS
You will find here the documents and presentation for our SRS.
SDD
You will find here the documents and presentation for our SDD.
Thesis
You will find here the documents and presentation for our Thesis
Document
Presentation
Accomplishments
Publications
Competitions
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Competition Title
type here detailss about your participation in the competition.