ITERATIVE CLASSIFIER FUSION
SYSTEM FOR THE DETECTION OF
ANDROID MALWARE
BY NAVANEETH KRISHNAN
PROBLEM
Big data has become ubiquitous in all aspects of modern society and in various research
domains. With mobile devices such as smartphones becoming capable to run intricate
software equivalent to that of personal computers (PCs), owners are leveraging their
smartphones for a wide variety of applications such as accessing and storing big data that
include sensitive and commercial-in-confidence data. Unfortunately, the rapid growth and
widespread user acceptance of smartphones have followed with a surge both in number
and complexity of malware that target popular mobile phone platforms.
SOLUTION
To address this problem, multi-classifier fusion systems have long been used to increase the
accuracy of malware detection for personal computers. However, previously developed
systems are quite large and they cannot be transferred to Android platform. We propose
Iterative Classifier Fusion System (ICFS), which is a system of minimum size, since it applies
a smallest possible number of classifiers. The system applies classifiers iteratively in fusion
with new iterative feature selection (IFS) procedure.
OBJECTIVE
The main objective of this project is to detect the malicious software that targets the
smartphones. When we get an APK file through another media, there is not an existing
system for analyse and verify an APK file that is good for our system. To enhance this
problem we propose Iterative Classifier Fusion System, which is a system of minimum size,
since it applies a smallest possible number of classifiers. The system applies classifiers
iteratively in fusion with new iterative feature selection procedure. Moreover, the graphical
user interface is provided in this system, which provides user to deal with the system very
easily.
SOFTWARE SPECIFICATION
Operating System : Windows 7 or above
Front End : Python, Django
Back End : SQlite
Tools : Pycharm 2020.1.4 , DBeaver 7.1
HARDWARE SPECIFICATION
Processor : i3 or above
RAM : 2 GB or above
Input devices : Mouse, Keyboard
Hard Disk : 512 GB
TYPES OF USERS
• Admin
• Customer
DATA FLOW DIAGRAMS
The DFD also known as bubble chart. It is a simple graphical formalism that can be used to
represent a system in terms of the input data to the system, various processing carried out
on these data and the output data generated by the system.
LEVEL 0
ADMIN LEVEL 1
USER LEVEL 1
DATABASE DESIGN(TABLES)
• Table 1: Name: Login
• Table 2: Name: user_details
• Table 3: Name: category_master
• Table 4: Name: training_set
• Table 5: Name: permission_settings
• Table 6: Name: user_apk
• Table 7: Name: apk_details
• Table 8: Name: manifest_details
• Table 9: Name: user_feedback
TABLE 1: NAME: LOGIN
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
user_id
Integer
Primary key
10
id
Uname
Varchar
Not null
50
Name
password
Varchar
Not null
50
Password
u_type
Varchar
Not null
50
User type
TABLE 2: NAME: USER_DETAILS
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
user_id
Interger
Primary key
10
To identify the
Fname
Varchar
Not null
150
user
First name of the
lname
Varchar
Not null
150
Last name of the
Gender
Varchar
Not null
50
user
Gender
Addr
Varchar
Not null
1500
Address of the
50
user
Pin code of the
user
Pin
Integer
Not null
user
Contact
Integer
Not null
50
Phone number
Email
Varchar
Not null
250
Email id
Status
Varchar
Not null
50
Status
TABLE 3: NAME: CATEGORY_MASTER
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
Category_id
Integer
Primary key
10
Category id
category_name
Varchar
Not null
150
Name of the
category
Descp
Varchar
Not null
1500
description
TABLE 4: NAME: TRAINING_SET
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
training_id
Integer
Primary key
10
training id
category_id
Varchar
Foreign key
10
To identify the
category
File
Varchar
Not null
1500
File
Dt
Date
Not null
150
Date
Tm
Time
Not null
50
Time
TABLE 5: NAME: PERMISSION_SETTINGS
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
Permission_id
Integer
Primary key
10
permission id
permission_descp
Varchar
Not null
1500
Permission
description
permission_class
Varchar
Not null
250
Permission class
Descp
Varchar
Not null
1500
Description
TABLE 6: NAME: USER_APK
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
User_apk_id
Integer
Primary key
10
Apk id
user_id
Integer
Foreign key
10
To identify the
user
file_path
Varchar
Not null
1500
File path
Dt
Date
Not null
50
Date
Tm
Time
Not null
50
Time
TABLE 7: NAME: APK_DETAILS
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
User_Id
Integer
Primary key
10
user id
User_apk_id
integer
Foreign key
10
To identify the
user’s Apk
file_name
Varchar
Not null
150
Name of the file
Content
Varchar
Not null
1500
Content
Result
Varchar
Not null
150
Result
TABLE 8: NAME: MANIFEST_DETAILS
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
User_id
Integer
Primary key
10
User id
user_apk_id
integer
Foreign key
10
To identify the
user’s apk
permission_details
Varchar
Not null
1500
Permission
details
m_class
Varchar
Not null
150
Model class
TABLE 9: NAME: USER_FEEDBACK
FIELD NAME
TYPE
KEY
SIZE
DESCRIPTION
Feedback_Id
Integer
Primary key
10
Feedback id
user_id
integer
Foreign key
10
To identify the
user
Msg
Varchar
Not null
1500
Message
Dt
date
Not null
50
Date
Tm
Time
Not null
50
Time
UI DESIGN - HOME
UI DESIGN – ADMIN LOGIN
UI DESIGN – REGISTRATION
UI DESIGN – APK UPLOAD
UI DESIGN – RESULT
UI DESIGN – FEEDBACK
THE END