Development of Case-Study on Online Fraud Detection Techniques

As the internet is becoming cheap and accessible for more people risk associated with it is also increasing. One of the most prominent threats is online fraud which could lead to the loss of all the hard-earned money of many people. There are various types of online fraud such as using malicious URL, credit card fraud, and online auction fraud. The size of the data is quite large so we can use different machine learning algorithms to improve the immunity towards these activities. This paper is related to the development of the case-study of various algorithms and their usage in the detection of malicious activities in case of online fraud. In this paper, we are going to compare various methodology and their applications.