Friday Squid Blogging: Ten-Foot Long Squid Washed onto Japanese Shore — ALIVE

This is rare:

An about 3-meter-long giant squid was found stranded on a beach here on April 20, in what local authorities said was a rare occurrence.

At around 10 a.m., a nearby resident spotted the squid at Ugu beach in Obama, Fukui Prefecture, on the Sea of Japan coast. According to the Obama Municipal Government, the squid was still alive when it was found. It is unusual for a giant squid to be washed ashore alive, officials said.

The deep-sea creature will be transported to Echizen Matsushima Aquarium in the prefectural city of Sakai.

Sadly, I do not expect the giant squid to survive, certainly not long enough for me to fly there and see it. But if any Japanese readers can supply more information, I would very much appreciate it.

BoingBoing <a href=”https://boingboing.net/2022/04/26/giant-squid-rescued-from-obama-in-japan.html>post. Video.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

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Video Conferencing Apps Sometimes Ignore the Mute Button

New research: “Are You Really Muted?: A Privacy Analysis of Mute Buttons in Video Conferencing Apps“:

Abstract: In the post-pandemic era, video conferencing apps (VCAs) have converted previously private spaces — bedrooms, living rooms, and kitchens — into semi-public extensions of the office. And for the most part, users have accepted these apps in their personal space, without much thought about the permission models that govern the use of their personal data during meetings. While access to a device’s video camera is carefully controlled, little has been done to ensure the same level of privacy for accessing the microphone. In this work, we ask the question: what happens to the microphone data when a user clicks the mute button in a VCA? We first conduct a user study to analyze users’ understanding of the permission model of the mute button. Then, using runtime binary analysis tools, we trace raw audio in many popular VCAs as it traverses the app from the audio driver to the network. We find fragmented policies for dealing with microphone data among VCAs — some continuously monitor the microphone input during mute, and others do so periodically. One app transmits statistics of the audio to its telemetry servers while the app is muted. Using network traffic that we intercept en route to the telemetry server, we implement a proof-of-concept background activity classifier and demonstrate the feasibility of inferring the ongoing background activity during a meeting — cooking, cleaning, typing, etc. We achieved 81.9% macro accuracy on identifying six common background activities using intercepted outgoing telemetry packets when a user is muted.

The paper will be presented at PETS this year.

News article.

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