New “Glowworm attack” recovers audio from devices’ power LEDs
Aug 2021, Ars Technica
The attack's complete passivity distinguishes it from similar approaches—a laser microphone can pick up audio from the vibrations on a window pane.
Image credit: Artist’s impression of the view through future night-vision glasses, Lei Xu and NTU
Machine learning algorithm revolutionizes how scientists study behavior
Sep 2021, phys.org
Pattern recognition becomes gait recognition, body position recognition and finally to straight behavior recognition. We're there.
B-SOiD -- Behavioral segmentation of open field in DeepLabCut -- discovers behaviors by identifying patterns in the position of an animal's body. The algorithm works with computer vision software and can tell researchers what behavior is happening at every frame in a video.
via Carnegie Mellon University: Alexander I. Hsu et al, B-SOiD, an open-source unsupervised algorithm for identification and fast prediction of behaviors, Nature Communications (2021). DOI: 10.1038/s41467-021-25420-x
In new cognitive research, people's eyes reveal that clichés are underrated
Oct 2021, phys.org
This is why fb is banking so hard on vr --
The research process centered on the fact that the pupil—the black dot at the center of the eye—dilates in response to emotionally charged or intellectually engaging experiences."Many people don't realize that the pupil expanding is an indication—a measurable indication—that you're more engaged," Goldberg said. Her previous work used fMRI brain scans to show that the amygdala, considered the emotional center in our brains, responds more to metaphors than literal language. This time, the researchers wanted tighter time controls. It takes a couple seconds for blood to flow to a new section of the brain and light up an fMRI scan, but pupils respond in a fraction of a second.
via Princeton University: Serena K. Mon et al, Conventional metaphors elicit greater real-time engagement than literal paraphrases or concrete sentences, Journal of Memory and Language (2021). DOI: 10.1016/j.jml.2021.104285
Study reveals scale of data-sharing from Android mobile phones
Oct 2021, phys.org
An in-depth analysis of a range of popular Android mobile phones has revealed significant data collection and sharing, including with third parties, with no opt-out available to users. They examined the data sent by six variants of the Android OS developed by Samsung, Xiaomi, Huawei, Realme, LineageOS and /e/OS.Even when minimally configured and the handset is idle, with the notable exception of e/OS, these vendor-customized Android variants transmit substantial amounts of information to the OS developer and to third parties such as Google, Microsoft, LinkedIn, and Facebook that have pre-installed system apps. There is no opt-out from this data collection.
Examples:
- The privacy focused e/OS variant of Android was observed to transmit essentially no data.
- The Xiaomi handset sends details of all the app screens viewed by a user to Xiaomi, including when and how long each app is used like the timing and duration of phone calls.
- The Huawei Swiftkey keyboard sends to Microsoft details of when a user is writing a text, using the search bar, or searching for contacts.
- Samsung, Xiaomi, Realme and Google collect long-lived device identifiers, e.g., the hardware serial number, alongside user-resettable advertising identifiers. This means that when a user resets an advertising identifier the new identifier value can be trivially re-linked back to the same device, potentially undermining the use of user-resettable advertising identifiers.
- Third-party system apps, e.g., from Google, Microsoft, LinkedIn and Facebook, are pre-installed on most of the handsets and silently collect data, with no opt out.
- There may exist a data ecosystem where data collected from a handset by different companies is shared/linked.
via Trinity College Dublin: Android Mobile OS Snooping By Samsung, Xiaomi, Huawei and Realme Handsets.
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