Data Mining Technique in Detecting and Predicting Cyber In Marketplace Sector

Abstract

Marketplace is one business solution that can be profitable, because it is not bound by time and place. However, marketplace can be misused by irresponsible parties, and can harm others. Then a pattern is needed to predict cybercrime in order to prevent it. To get a pattern, we can use data mining. This paper presents a general idea about the model of Data Mining techniques and diverse cybercrimes in market place applications. This paper implements data mining techniques like K-Means, Influenced Association Classifier and J48 Prediction tree for investigating the cybercrime data sets. K-means selects the initial centroids so that the classifier can mine the record and also formulate predictions of cybercrimes with J48 algorithm. The knowledge of K-Means, Influenced Association Classifier and also J48 Prediction tree tends certainly to afford a enhanced, incorporated, and precise result over the cybercrime prediction in the marketplace sectors and prevent the cybercrime.