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Credit card fraud detection

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This document proposes a mechanism to detect credit card fraud in online transactions using a Hidden Markov Model. The model would classify users as having low, medium, or high spending habits and flag transactions as potentially fraudulent if a user makes a payment outside their normal spending category. The mechanism was implemented using HTML, CSS, JavaScript, PHP, and MySQL and could help reduce fraud by adding an additional layer of security validation for online payments. However, it may not detect all fraudulent transactions accurately as the Hidden Markov Model requires at least 10 prior transactions to properly classify users.

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Credit Card Fraud Detection
Contents • Introduction • Problem Definition • Proposed Solution • Block Diagram • Implementation • Software and Hardware Requirements • Benefits • Results and Conclusion
Introduction • Online Shopping – one of the largest and fast going trend • Mode of payment – credit card, debit card, Net Banking • Online payment does not require physical card • Major Risk – credit /debit card detail is known to other
Problem Definition • Online payment does not require physical card • Anyone who know the details of card can make fraud transactions • Currently, card holder comes to know only after the fraud transaction is carried out. • No mechanism to track the fraud transaction
Proposed Solution • A mechanism is developed to determine whether the given transaction is fraud or not • The mechanism uses Hidden Markov Model to detect fraud transaction • Hidden Markov Model works on the basis of spending habit of user. • Classifies user into Low, Medium or High category
Block Diagram User e-Commerce Website Bank FDS
Implementation • Project is implemented using following technologies : HTML, CSS, JavaScript, PHP and MySQL • HTML and CSS is used for interface designing • JavaScript is used for client side validation • PHP is used for server side scripting • MySQL is used for database
Hardware & Software Req. Online Auction System • Pentium Core 2 Duo processor or above • I GB RAM • 20 GB HDD • Router for Internet Connection • Windows 2000/ Windows XP/ Windows Vista/ Windows 7 • WAMP • Macromedia Dreamweaver
Benefits • Reduction in number of fraud transaction • User can safely use his credit / debit card for online transaction • Added layer of security
Results and Conclusion • Fraud detection is based on Hidden Markov Model which is learning algorithm, hence not 100% correct • It has detected those transaction as fraud where user belongs to low category and high category payment is made or vice versa • The mechanism require at least 10 transaction to determine accurately the transaction as fraud or not.
Credit card fraud detection

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Credit card fraud detection

  • 2. Contents • Introduction • Problem Definition • Proposed Solution • Block Diagram • Implementation • Software and Hardware Requirements • Benefits • Results and Conclusion
  • 3. Introduction • Online Shopping – one of the largest and fast going trend • Mode of payment – credit card, debit card, Net Banking • Online payment does not require physical card • Major Risk – credit /debit card detail is known to other
  • 4. Problem Definition • Online payment does not require physical card • Anyone who know the details of card can make fraud transactions • Currently, card holder comes to know only after the fraud transaction is carried out. • No mechanism to track the fraud transaction
  • 5. Proposed Solution • A mechanism is developed to determine whether the given transaction is fraud or not • The mechanism uses Hidden Markov Model to detect fraud transaction • Hidden Markov Model works on the basis of spending habit of user. • Classifies user into Low, Medium or High category
  • 7. Implementation • Project is implemented using following technologies : HTML, CSS, JavaScript, PHP and MySQL • HTML and CSS is used for interface designing • JavaScript is used for client side validation • PHP is used for server side scripting • MySQL is used for database
  • 8. Hardware & Software Req. Online Auction System • Pentium Core 2 Duo processor or above • I GB RAM • 20 GB HDD • Router for Internet Connection • Windows 2000/ Windows XP/ Windows Vista/ Windows 7 • WAMP • Macromedia Dreamweaver
  • 9. Benefits • Reduction in number of fraud transaction • User can safely use his credit / debit card for online transaction • Added layer of security
  • 10. Results and Conclusion • Fraud detection is based on Hidden Markov Model which is learning algorithm, hence not 100% correct • It has detected those transaction as fraud where user belongs to low category and high category payment is made or vice versa • The mechanism require at least 10 transaction to determine accurately the transaction as fraud or not.