The document proposes a methodology called Mobsafe for evaluating mobile apps using cloud computing and data mining to filter out malware. It outlines a hybrid approach combining static and dynamic analysis for enhanced security, utilizing a cloud infrastructure with tools for automated analysis. Future enhancements may include web mining and machine learning techniques for improved malware detection.

1. Mobsafe: Using Cloud computing and Data mining
Name: sowmya Bk
Email id: sowmya.harshini@gmail.com
University: VTU
Sem: 2nd
Branch : software engg (M.tech)

2. Introduction
 With the explosive increase in mobile apps,more and more threats
Migrate from traditional PC to mobile devices.
 we propose a methodology to evaluate mobile apps based on cloud
computing and data mining.
 Our evaluation results show that its practical use of cloud platform and
data mining to verify all stored apps routenely and filter out malware apps
from mobile app markets

3.  Mobile Threats.
 Some root causes for android malware origins.
 some known malwares in android platform.
Static and dynamic behavior analysis.

4. Existing system
 Permission based method was using for identifying
malwares.
 Semantics-Aware based technique was used.

5. Proposed System
 In this work a methodology is being proposed which
provides security to your mobile phone from malwares .
 It includes combination of dynamic and static methods
to provide security.
 It includes data mining techniques.
 It includes some method that is used to provide optimized
outputs.

6. Mobsafe
 It has infrastructure cloud platfarm
 It has cloud stack(home-brewed platform).
Hadoop storage for mobile apps.
 Work principle
 Mobsafe is a system to check whether an android app is virulence
based on some tools in cloud platfarm it will verify the malware.
 Mobsafe is an automatize system which can be used to analyze
android apps.

7. Infrastructure cloud platform based on CloudStack.
Architecture

8. The procedure of Android analysis in Mobsafe.

9.  Mobsafe has a web frontend.
 Mobsafe has two backend tools , They are ASEF and SAAF.
 ASEF is an automates tool which can be used to analyze
Android apps by using ADB and AVD.
 SAAF is static analyzer for android apk files.

10. Interest Area
As the future perspective some web mining and more
advanced data mining techniques will be implemented to
get more optimized outputs.
I would like to implement Machine learning is a
promising technology to identify mobile apps
virulence based on data mining.
 If I get internship I would like to work on mobile
application domain and Testing/