Paper Contents
Abstract
Recent research has revealed an alarming prevalence of click fraud in online advertising systems. In this project, after investigation of different known categories of Web-bots along with their malicious activities and associated threats, we distinguish between the important behavioral characteristics of bots versus humans in conducting click fraud with in modern-day ad platforms performance in terms of accuracy and prediction-recall rate. Subsequently, we provide an overview of the current detection and threat mitigation strategies pertaining to click fraud. The proposed algorithm is tested by extensive experiments using real-world data. Compared with the state-of-art machine learning algorithms, our model can achieve significant.
Copyright
Copyright © 2023 PARKAVI G. This is an open access article distributed under the Creative Commons Attribution License.
