Iodine-containing volatiles are major degradation products of halide perovskite materials under irradiation, yet iodine diffusion kinetics into and throughout organic hole transport materials (HTMs) and consequent reactions are largely unexplored. Here, we modify the Ca:O2 corrosion test to Ag:I2 to quantify I2 transmission rates through common organic HTMs. We observe I2 permeability to inversely correlate with HTM ionization energy, or the highest occupied molecular orbital (HOMO) energy. Tracking electronic conductance during exposure to I2 confirms shallow HOMO HTMs are strongly oxidized (i.e., doped), leading to substantial I2 uptake and increased transmission rates. Finally, relationships between HOMO level, doping, and transmission rate are maintained when methyl­ammonium lead triiodide (MAPbI3) photolysis products are the only source of iodine. While HTM energetics influence the initial performance of halide perovskite devices by selective charge extraction, our results further suggest they will affect device stability; deeper HOMO energy HTMs will suppress iodine migration and associated degradation mechanisms.

Tor is the most well-known tool for circumventing censorship. Unfortunately, Tor traffic has been shown to be detectable using deep-packet inspection. WebRTC is a popular web framework that enables browser-to-browser connections. Snowflake is a novel pluggable transport that leverages WebRTC to connect Tor clients to the Tor network. In theory, Snowflake was created to be indistinguishable from other WebRTC services.In this paper, we evaluate the indistinguishability of Snowflake. We collect over 6,500 DTLS handshakes from Snowflake, Facebook Messenger, Google Hangouts, and Discord WebRTC connections and show that Snowflake is identifiable among these applications with 100% accuracy. We show that several features, including the extensions offered and the number of packets in the handshake, distinguish Snowflake among other WebRTC-based services. Finally, we suggest recommendations for improving identification resistance in Snowflake. The dataset used is publicly available.

Video conferencing applications (VCAs) have become a critical Internet application, even more so during the COVID-19 pandemic, as users worldwide now rely on them for work, school, and telehealth. It is thus increasingly important to understand the resource requirements of different VCAs and how they perform under different network conditions, including: how much "speed" (upstream and downstream throughput) a VCA needs to support high quality of experience; how VCAs perform under temporary reductions in available capacity; how they compete with themselves, with each other, and with other applications; and how usage modality (e.g., number of participants) affects utilization. We study three modern VCAs: Zoom, Google Meet, and Microsoft Teams. Answers to these questions differ substantially depending on VCA. First, the average utilization on an unconstrained link varies between 0.8 Mbps and 1.9 Mbps. Given temporary reduction of capacity, some VCAs can take as long as 50 seconds to recover to steady state. Differences in proprietary congestion control algorithms also result in unfair bandwidth allocations: in constrained bandwidth settings, one Zoom video conference can consume more than 75% of the available bandwidth when competing with another VCA (e.g., Meet, Teams). For some VCAs, client utilization can decrease as the number of participants increases, due to the reduced video resolution of each participant's video stream given a larger number of participants. Finally, one participant's viewing mode (e.g., pinning a speaker) can affect the upstream utilization of other participants.

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