Document Fraud Detection with the help of Data Mining and Secure Substitution Method with Frequency Analysis

Prevention of fraud and abuse has become a major concern of many organizations. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will usually find ways to circumvent such measures. Detecting fraud is essential once prevention mechanism has failed. Several data mining algorithms have been developed that allow one to extract relevant knowledge from a large amount of data like fraudulent financial statements to detect. In this paper we present an efficient approach for fraud detection. In our approach we first maintain a log file for data which contain the content separated by space, position and also the frequency. Then we encrypt the data by substitution method and send to the receiver end. We also send the log file to the receiver end before proceed to the encryption which is also in the form of secret message. So the receiver can match the data according to the content, position and frequency, if there is any mismatch occurs, we can detect the fraud and does not accept the file.