Published Paper Details:

Data mining techniques have been used extensively to detect insurance fraud and financial fraud, which is a growing area of tremendous importance. Financial deception will pay special attention to spotting fraudulent credit card transactions. Credit utilisation Due to significant advancements in internet commerce, the use of credit cards has expanded dramatically. Technology. Credit cards have become the most popular method of payment for both online and offline purchases. As with any ordinary purchase, the number of incidences of fraud related with it is increasing by the day. In this Using a Hidden Markov Model to sequence operations in credit card transaction processing (HMM) and demonstrate how it might be used to detect fraud. Initially, an HMM is trained with a cardholder's regular behaviour. An incoming credit card transaction is considered fraudulent if the trained model does not accept it with a high enough probability. It also ensures that legitimate transactions are not denied. Credit cards are one of the most convenient methods of payment when shopping online. Payment is made by providing information such as the card number, security code, and expiration date of the credit card while shopping online. Every cardholder's spending method is modelled using HMM to correct the risk elements of using the credit card. Data encryption is commonly used to protect sensitive data from security threats such as "attacks on confidentiality. "In the present, Large text messages need a long time to encrypt before they can be transferred, causing a delay in subsequent information transmission. Security dangers include those that occur during the transmission of secret information across insecure communication networks.