AdRemover: The Improved Machine Learning Approach for Blocking Ads

Thu Vo
Prof. Chetan Jaiswal, Faculty Mentor

There is an explosion in the advertisements over web nowadays. Most of the websites we visit contain ads, even Facebook and Google. Incidents like ads that show up with the content exactly what you have been searching not long ago is the cause of someone is spying on us. Such events happen as a result of Web Tracking. Ads were meant to support businesses to market their products. However, some of these have allowed ads as malvertisements, which may take advantage of these functionalities to steal the users sensitive information. Most of AdBlockers do not provide the depth of functionality and intelligence required to block all the undesirable content because several of them are using outdated filter-lists. We propose our tool, AdRemover, that is a novel machine learning approach using the list of Ad and Non-Ad URLs as the dataset, then updating its filter lists if there is any new Ad detected. Our classification applying Random Forest which exceeds 97.7% of accuracy.

Keywords: Security, Machine Learning, AdBlock, Malvertisement, Malware

Topic(s):Computer Science

Presentation Type: Oral Presentation

Session: TBA
Location: TBA
Time: TBA