Malware detection based on permissions on android platform using data mining

Other Title(s)

استكشاف البرامج الخبيثة اعتمادا على الصلاحيات على منصة أندرويد باستخدام تنقيب البيانات

Dissertant

Nasman, Muhammad Ishaq Ibrahim

Thesis advisor

Barhum, Tawfiq Sulayman

Comitee Members

Fatayir, Tamir Sad
al-Halis, Ala Mustafa

University

Islamic University

Faculty

Faculty of Information Technology

Department

Information Technology

University Country

Palestine (Gaza Strip)

Degree

Master

Degree Date

2016

English Abstract

With the spreading of smart mobile devices to nearly every person, Android Operating System is dominating the mobile’s operating systems.

Due to the weak policy of submitting application to Google Play store, attackers developed malware to attack the users of the Android operating system with malware application or by including malicious code into applications.

Researches have been done in this area, but solutions required installing the applications to monitor the malware behavior, or by taking actions after installing the application.

We proposed a new method using Data Mining to detect newly and unknown malware using the applications’ permissions as base features.

In order to create binary dataset we collected from benign and malware android app samples, the dataset consist of five different features collected based on different number of attributes and conditions.

Different evaluation measure used to evaluate the proposed method, the results show that we achieved 96.74% with f-measure and 99.3% with area under the Receiver Operating Characteristic ROC curve

Main Subjects

Information Technology and Computer Science

No. of Pages

56

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-727255