crime detection
TRANSCRIPT
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CRIME DETECTION
PRESENTED BY:ANKUSH DEEP11SBSCA009
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ABSTRACT
About: Identity crime is well known, prevalent, and costly and credit application
fraud is a specific case of identity crime. The existing non-data mining detection systems of business rules and scorecards, and known fraud matching have limitations.
Solution: To address these limitations and combat identity crime in real-time, this paper proposes a new multi-layered detection system complemented with additional layer Communal Detection. CD finds real social relationships to reduce the suspicion score, and is tamper-resistant to synthetic social relationships. It is the whitelist-oriented approach on a fixed set of attributes. The CD algorithm matches all links against the whitelist to find communal relationships and reduce their link score. CD can detect more types of attacks, better account for changing legal behavior.
Technology Used :
- jdk 1.7(NetBeans IDE 7.3.1) - Apache Tomcat 7.0(Web Server)
-MySQL as backend.
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INTRODUCTION At one extreme, synthetic identity fraud refers to the use of plausible but
fictitious identities.
Real identity theft refers to illegal use of innocent people’s complete identity details. These can be harder to obtain (although large volumes of some identity data are widely available) but easier to successfully apply.
As in identity crime, credit application fraud has reached a critical mass of fraudsters who are highly experienced, organized, and sophisticated .Their visible patterns can be different to each other and constantly change.
To provide confidentiality and security so that fraudsters can be stopped.
A reliable and compositional attempt of letting not the illegal things happen.
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OBJECTIVE
Synthetic Identity fraud and real identity theft should be stopped .
The main motto behind this is to stop fraudsters rom using innocent peoples identity and misusing it for their illegal works.
existing non-data mining detection systems of business rules and scorecards, and known fraud matching have limitations. To address these limitations and combat identity crime in real-time, this paper proposes a new multi-layered detection system complemented with additional layer Communal Detection.
CD finds real social relationships to reduce the suspicion score, and is tamper-resistant to synthetic social relationships. It is the whitelist-oriented approach on a fixed set of attributes.
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EXISTING SYSTEM
The first existing defense is made up of business rules and scorecards. In Australia, one business rule is the hundred-point physical identity check test which requires the applicant to provide sufficient point-weighted identity documents face-to-face.
They must add up to at least one hundred points, where a passport is worth seventy points. Another business rule is to contact (or investigate) the applicant over the telephone or Internet.
The above two business rules are highly effective, but human resource intensive. To rely less on human resources, a common business rule is to match an application’s identity number, address, or phone number against external databases.
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PROPOSED SYSTEM
Identity crime has become prominent because there is so much real identity data available on the Web, and confidential data accessible through unsecured mailboxes.
There are two types of duplicates: exact (or identical) duplicates have the all same values; near (or approximate) duplicates have some same values (or characters), some similar values with slightly altered spellings, or both.
Here we use communal detection algorithm. To account for legal behavior and data errors, Communal Detection (CD) is the whitelist-oriented approach on a fixed set of attributes.
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SYSTEM MODULES
Credit module: Credit applications are Internet or paper-based forms with written requests by potential customers for credit cards, mortgage loans, and personal loans. Users should submit identity details and it must be original. To reduce identity crime, the most important textual identity attributes such as personal name, fathers name, date of birth, mobile number, Address, Email id must be used in credit application.
Making Whitelist: CD finds real social relationships to reduce the suspicion score, and is tamper-resistant to synthetic social relationships.
Verification Module: In this module loan provider verify the user identity details.
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SYSTEM SPECIFICATION
H/W System Configuration:- Processor - Pentium –III Speed - 1.1 Ghz RAM - 256 MB(min) Hard Disk - 20 GB Floppy Drive - 1.44 MB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA
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S/W System Configuration:- Operating System :Windows95/98/2000/XP Application Server : Tomcat5.0/6.X Front End : HTML, Java, Jsp Scripts : JavaScript. Server side Script : Java Server Pages. Database : Mysql Database Connectivity : JDBC.
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SYSTEM DESIGN
Check
unauthorized user
Yes No
End Process
ADMIN
Backup make whitelist
s
verify identitydetails
ADMIN DFD
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Check
unauthorized user
Yes No
sumbit identity details
End Process
login
user
Registration
apply loan
check status
USER DFD
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ADMIN
UserLogin
USER
User Registration
check status
view users details
verify user
give identity details
apply loan
back up
verify user details
make whitelist
USE CASE DIAGRAM
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SAMPLE SCREENS
HOMEPAGE
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USER REGISTRATION PAGE
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USER LOGIN PAGE
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PERSONAL DETAILS FOR LOANS
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LOAN APPLICATION FORM
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CHECK STATUS
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CHANGE PASSWORD PAGE
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NEW APPLICATION FOUND
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ADMIN VERIFYING USERS
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ADMIN VERIFYING USER DETAILS
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USER ACCEPTED BY ADMIN
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BACKUP
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APPLY LOAN
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CHECK STATUS
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CONCLUSION
Our detection system describes an important domain that has many problems relevant to other data mining research. It has documented the development and evaluation in the data mining layers of defence for a real-time credit application fraud detection system.
The implementation of CD algorithms is practical because these algorithms are designed for actual use to complement the existing detection system. Nevertheless, there are limitations.
The overall implementation of crime detection is to make sure that the crime using innocent peoples documents should be taken care of handled properly.
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FUTURE ENHANCEMENT
Hierarchy modification/additional capabilities are inbuilt in the system.
Dynamic screens/web page according to requirement can be introduced any time.
System is very flexible for future modifications.
The modifications and changings can be done by adding more features to it for
advanced form of verification.
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THANK YOU