TO VIEW OUTPUT OF THIS PROJECT CLICK HERE:
ABSTRACT:
The
popularity and advanced functionality of mobile devices has made them
attractive targets for malicious and intrusive applications (apps). Although
strong security measures are in place for most mobile systems, the area where
these systems often fail is the reliance on the user to make decisions that
impact the security of a device. As our prime example, Android relies on users
to understand the permissions that an app is requesting and to base the
installation decision on the list of permissions. Previous research has shown
that this reliance on users is ineffective, as most users do not understand or
consider the permission information. We propose a solution that leverages a
method to assign a risk score to each app and display a summary of that
information to users.
Results
from four experiments are reported in which we examine the effects of
introducing summary risk information and how best to convey such information to
a user. Our results show that the inclusion of risk-score information has
significant positive effects in the selection process and can also lead to more
curiosity about security-related information.
EXISTING SYSTEM:
The
GPS unit can tell exactly where you are, while the microphone can record audio,
and the camera can record images. Additionally, mobile devices are often linked
directly to some monetary risks, via SMS messages, phone calls, and data plans,
which can impact a user’s monthly bill, or increasingly, as a means to
authenticate to a bank or directly link to a financial account through a
‘digital wallet’. In Android an app must request a specific permission to be allowed
access to a given resource. Android warns the user about permissions that an
app requires before it is installed, with the expectation that the user will
make an informed decision. The effectiveness of such a defense depends to a
large degree on choices made by the users.
Indeed
whether an app is considered too invasive or not may depend on the user’s
privacy preference. It presents information which is more technical that is not
understandable by the ordinary users.
DISADVANTAGES OF
EXISTING SYSTEM:
·
It presents the summary of permissions
that the app uses to the user in more abstract way that was not easily
understood by the user.
·
Allows the user to install unsecure
application that causes damage to the user data.
PROPOSED SYSTEM:
We
propose the addition of a summary risk rating for each app. A summary risk
rating enables easy risk comparisons among apps that provide similar
functionalities. We believe that one reason why current permission information is
often ignored by users is that it is presented in a “standalone” fashion and in
a way that requires a lot of technical knowledge and time to distill useful
information, making comparison across apps difficult. An important feature of the
mobile app ecosystem is that users often have choices and alternatives when
choosing a mobile app. If a user knows that one app is significantly riskier
than another but
provides
the same or similar functionality, then this fact may cause the user to choose
the less risky one. This will in turn provide incentives for developers to
better follow the least-privilege principle and request only necessary
permissions. The method can rank the risk of any Android app among all apps
available in Google Play, Google’s online market for Android apps. Such a risk
ranking can be translated into categorical values such as very low, low,
medium, and high risk, to provide a summary risk rating.
ADVANTAGES OF PROPOSED
SYSTEM:
·
It present the summary of permissions
required for the app in more simple way so that user can ignore unsecure
application.
·
It provides comparison of two
applications to find out which application is secure than other.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
ü Processor - Pentium –IV
ü Speed - 1.1 Ghz
ü RAM - 512 MB(min)
ü Hard
Disk - 40 GB
ü Key
Board - Standard Windows Keyboard
ü Mouse - Two or Three Button Mouse
ü Monitor - LCD/LED
SOFTWARE REQUIREMENTS:
•
Operating system : Android
•
Coding Language : Android SDK
•
Data Base : SQLite
•
Tool : Eclipse
REFERENCE:
Christopher
S. Gates, Jing Chen, Ninghui Li and Robert W. Proctor “EFFECTIVE RISK COMMUNICATION FOR ANDROID APPS”
IEEE
TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 11, NO. 3, MAY-JUNE 2014
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