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

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.