ABSTRACTConventional ad blocking and tracking prevention tools often fall short in addressing web content manipulation. Machine learning approaches have been proposed to enhance detection accuracy, yet aspects of practical deployment have frequently been overlooked. This paper introduces AdFlush, a novel machine learning model for real-world browsers. To develop AdFlush, we evaluated the effectiveness of 883 features, ultimately selecting 27 key features for optimal performance. We tested AdFlus...