Ross Teixeira

Shaanan Cohney, Ross Teixeira, Anne Kohlbrenner et al.

Universities have been forced to rely on remote educational technology to facilitate the rapid shift to online learning. In doing so, they acquire new risks of security vulnerabilities and privacy violations. To help universities navigate this landscape, we develop a model that describes the actors, incentives, and risks, informed by surveying 49 educators and 14 administrators at U.S. universities. Next, we develop a methodology for administrators to assess security and privacy risks of these products. We then conduct a privacy and security analysis of 23 popular platforms using a combination of sociological analyses of privacy policies and 129 state laws, alongside a technical assessment of platform software. Based on our findings, we develop recommendations for universities to mitigate the risks to their stakeholders.

Jordan Holland, Ross Teixeira, Paul Schmitt et al.

In this paper, we develop a method to create a large, labeled dataset of visible network device vendors across the Internet by mapping network-visible IP addresses to device vendors. We use Internet-wide scanning, banner grabs of network-visible devices across the IPv4 address space, and clustering techniques to assign labels to more than 160,000 devices. We subsequently probe these devices and use features extracted from the responses to train a classifier that can accurately classify device vendors. Finally, we demonstrate how this method can be used to understand broader trends across the Internet by predicting device vendors in traceroutes from CAIDA's Archipelago measurement system and subsequently examining vendor distributions across these traceroutes.