Representing Fine-Grained Co-Occurrences for Behavior-Based Fraud Detection in Online Payment Services

Aim:

        The main aim of the project is to identify the Credit card Fraud transaction that has been initiated by the any user and to avoid that type of transaction.

Synopsis:

       The rapid increase of online transaction has given rise to a significant amount. However, the Internet environment is open, online shopping systems have bugs, and criminals can use some bad techniques such as Trojan and pseudo base-station. All these result in a serious increasing of credit card fraud events. When a criminal steals or cheats the information of the credit card of a cardholder, the criminal can use the credit card to consume. According to the Nilsson Report in October 2016, more than $31 trillion were generated worldwide by online payment systems in 2015, increasing 7.3% than 2014. Worldwide losses from credit card fraud rose to $21 billion in 2015, and will possibly reach $31 billion by 2020. Our proposed model will used in order to avoid these fraud transactions.

Existing System:

        In Existing the transaction will be successful once if the user enters the correct pin pass of that particular card but there is a drawback as server will not identify the user and process the user transaction but that transaction might be done any false user as in online transaction there is lot of security issues. As there is advanced technology that user to hack the user credit card detail including user pin number.

Problem Definition:

• It is very hard for server to identify the transaction done by authorized user or not
• Server will only validate the user based on the user entered pin number.

Challenges:

• Maintain user transaction detail for each user.
• Identify the Transaction based on the history

Proposed System:

       To Identify the Fraud transaction server need to maintain user transaction data like transaction processed location, merchant name, and amount of transaction that process based on these server will maintain the transaction data. During transaction the server will save the information like amount and location from where the transaction takes place. If a transaction takes place from a new location the server sends the information to credit card user for second level authentication. After second level authentication is done the transaction takes place so that we can avoid credit card fraud.