Hello, my name is Bezal Osad. I'm APHD candidate here at Florida International University CEC Lab, and I'm here to introduce our paper title Breaking the Bot Barrier, evaluating adversarial AI techniques against multimodal defense models, where it has been accepted for a short paper track of a same web conference 2024. I would like to thank my co-authors, especially my advisor, Dr. Kairos. We know that there has been a trend to use behavior of the visitors, or clients, to detect whether or not they are bot or human. Such solutions include Google recapture and Hcapture, where the behavior of the visitor is used to determine their identity. In this work, we propose a multimodal detection model where we not only use mouse movement events, but also incorporate different kinds of events, including over 40 browser events. Such as clicks, keep keyboard events, and different types of events. As you can see in the form, there is a simple login scenario where the user moves the mouse, clicks on different fields of the form, types their credentials, and finally submit to result in such a sequence of events. We take this sequence and use an LSTM model to train our detection model. Additionally, we go over the adversarial side of the paper, where we try to apply different adversarial techniques like FGSM and brute force to manipulate the model into misclassifying the modified sequence. Specifically, we record sequence of events from bots, then we try to run our adversarial attacks and to generate a modified sequence, which is misclassified as human by the model. Finally, we discuss the practicality of the attacks and how they can be applied in aerial work. Thank you.