The success of generative AI relies heavily on training on data scraped through extensive crawling of the Internet, a practice that has raised significant copyright, privacy, and ethical concerns. While few measures are designed to resist a resource-rich adversary determined to scrape a site, crawlers can be impacted by a range of existing tools such as robots.txt, NoAI meta tags, and active crawler blocking by reverse proxies. In this work, we seek to understand the ability and efficacy of today's networking tools to protect content creators against AI-related crawling. For targeted populations like human artists, do they have the technical knowledge and agency to utilize crawler blocking tools such as robots.txt, and can such tools be effective? Using large scale measurements and a targeted user study of 203 professional artists, we find strong demand for tools like robots.txt, but significantly constrained by critical hurdles in technical awareness, agency in deploying them, and limited efficacy against unresponsive crawlers. We further test and evaluate network level crawler blockers provided by reverse proxies. Despite relatively limited deployment today, they offer stronger protections against AI crawlers, but still come with their own set of limitations.

Canvas fingerprinting is an effective technique for implicitly re-identifying visitors to a Web site based on subtle variations in the graphical rendering of specific "test canvases". Different fingerprinting actors make use of distinct canvases for this purpose and thus, as we show, it is possible to ''fingerprint the fingerprinters'' by grouping together identical canvases that are employed for these tests. In this paper, we document the prevalence of canvas fingerprinting (finding that 12.7% of the top 20K sites engage in it), use this grouping technique to measure and characterize the online footprint of widely-used fingerprinting services, and finally analyze the context in which these services are used to shine light on their intended purpose.

This paper empirically evaluates the efficacy of two ubiquitous forms of enterprise security training: annual cybersecurity awareness training and embedded anti-phishing training exercises. Specifically, our work analyzes the results of an 8-month randomized controlled experiment involving ten simulated phishing campaigns sent to over 19,500 employees at a large healthcare organization. Our results suggest that these efforts offer limited value. First, we find no significant relationship between whether users have recently completed cybersecurity awareness training and their likelihood of failing a phishing simulation. Second, when evaluating recipients of embedded phishing training, we find that the absolute difference in failure rates between trained and untrained users is extremely low across a variety of training content. Third, we observe that most users spend minimal time interacting with embedded phishing training material in-the-wild; and that for specific types of training content, users who receive and complete more instances of the training can have an increased likelihood of failing subsequent phishing simulations. Taken together, our results suggest that anti-phishing training programs, in their current and commonly deployed forms, are unlikely to offer significant practical value in reducing phishing risks.