Proposal
SRS
SDD
Thesis
Team Members

Seif ElDein Mohamed
Team Leader

Mostafa Ashraf
Team Member

Amr Ehab
Team Member

Omar Shereef
Team Member
Supervisors

Eslam Amer
Associate Professor

Haytham Tarek
Teaching Assistant

Mostafa Badr
Teaching Assistant

Abstract
The mobile industry is in rapid evolution making smartphones available with affordable rates for all segments of society. Smartphones’ purposes are not limited to making phone calls or sending messaging, users can also take photos, store personal data, do online banking and trace their daily activities. The more applications appear, the more security becomes a concern to mobile users. This concern arises from the fear of being subjected to a security breach that jeopardizes confidential personal data such as emails, passwords, location, credentials etc. Malware applications which are developed for the sake of compromising users’ personal data are also increasing rapidly day after day. In our work, we aim to design an intelligent detection framework for Android malware applications. The framework uses different analysis-based approaches along with different machine learning algorithms to distinguish between benign and malicious

System Objectives
1-To use different machine learning algorithms to detect malicious Android applications based on permissions and API Calls.
2-To provide firewall from breaching Android users’ critical data.
3-To secure the personal data information.

System Scope
The proposed system classifies malware behaviors of Android Applications with efficiency and viability, utilizing machine learning techniques and to determine the ability of malware, detect it, and contain it. It additionally helps in determining recognizable examples that can be utilized to fix and prevent future infections.
Documents and Presentations
Proposal
You will find here the documents and presentation for our proposal.
Document
Presentation
SRS
You will find here the documents and presentation for our SRS.
Document
presentation
SDD
You will find here the documents and presentation for our SDD.
Document
presentation
Thesis
You will find here the documents and presentation for our Thesis
Document
Presentation
Accomplishments
Publications
Competitions

Detecting Malicious Android Applications Based On API calls and Permissions Using Machine learning Algorithms

Competition Title
Detail Text