In Deep Trouble: Bot Prevention in the Age of Deep Learning

Jason Polakis, Assistant Professor, Computer Science Department, University of Illinois at Chicago

Abstract: 

Recent advancements in deep learning have demonstrated impressive results. These techniques have direct application in many areas that rely on computer vision and speech recognition, and are being increasingly adopted by major tech companies. However, the wide availability of deep learning systems and online services has also rendered these capabilities freely accessible to cyber-criminals. In this talk I will focus on the significant impact of deep learning attacks against CAPTCHAs, which typically constitute the first line of defense against automated bot activities. To that end, I will present recent work in which we used deep learning services to deploy highly effective low-cost attacks against the most prevalent CAPTCHA services. First, I will outline our attacks against Google’s image ReCaptcha, the first CAPTCHA-breaking attack to extract semantic information from images. Next, I will detail how we used speech recognition services to create effective generic solvers for audio CAPTCHAs. Finally, I will discuss the long term implications for CAPTCHA design, as we have appear to have reached a point where attempting to distinguish humans from bots through straightforward tasks is unrealistic.

Jason Polakis, Assistant Professor, Computer Science Department, University of Illinois at Chicago

Jason Polakis is an Assistant Professor in the Computer Science Department at the University of Illinois at Chicago. He received his B.Sc. (2007), M.Sc. (2009), and Ph.D. (2014) degrees in Computer Science from the University of Crete, Greece, while working as a research assistant in the Distributed Computing Systems Lab at FORTH.

Prior to joining UIC, Jason was a postdoctoral research scientist in the Computer Science Department at Columbia University, and a member of the Network Security Lab.

BibTeX
@conference {215323,
author = {Jason Polakis},
title = {In Deep Trouble: Bot Prevention in the Age of Deep Learning},
year = {2018},
address = {Atlanta, GA},
publisher = {{USENIX} Association},
month = may,
}