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Submission + - Study shows which messengers leak your data, drain your battery, and more (arstechnica.com)

Submitted by AmiMoJo
AmiMoJo writes: Link previews are a ubiquitous feature found in just about every chat and messaging app, and with good reason. They make online conversations easier by providing images and text associated with the file that’s being linked. Unfortunately, they can also leak our sensitive data, consume our limited bandwidth, drain our batteries, and, in one case, expose links in chats that are supposed to be end-to-end encrypted. Among the worst offenders, according to research published on Monday, were messengers from Facebook, Instagram, LinkedIn, and Line. More about that shortly. First a brief discussion of previews.

Facebook Messenger and Instagram both downloaded a 2.6GB test file, as well as executing arbitrary Javascript code on their servers. When informed of this Facebook (which owns Instagram) said that was the intended behaviour, even though it could be used to e.g. hijack their servers for cryptocurrency mining.

The three best messaging platforms were Signal, WhatsApp, Threema and iMessage, at least in terms of properly protecting your personal data.

Comment Re:Embarrassing Drink Preferences Come to Light (Score 1) 15

by JGrizz (#60351273) Attached to: Alcohol Delivery Service Drizly Confirms Data Breach
Fortunately, white claw didn't come until 2016, at which point I'd already been burned enough by flavored malt beverages to keep my distance. On a side note, I just came across this article in The Atlantic: The Justice Department Explains Why Bud Light Lime-a-Rita Is a 'Premium-Plus' Beer. ....

Submission + - New Imaging System Creates Pictures By Measuring Time (phys.org)

Submitted by Anonymous Coward
An anonymous reader writes: Photos and videos are usually produced by capturing photons—the building blocks of light—with digital sensors. For instance, digital cameras consist of millions of pixels that form images by detecting the intensity and color of the light at every point of space. 3-D images can then be generated either by positioning two or more cameras around the subject to photograph it from multiple angles, or by using streams of photons to scan the scene and reconstruct it in three dimensions. Either way, an image is only built by gathering spatial information of the scene. In a new paper published today in the journal Optica, researchers based in the U.K., Italy and the Netherlands describe an entirely new way to make animated 3-D images: by capturing temporal information about photons instead of their spatial coordinates.

Their process begins with a simple, inexpensive single-point detector tuned to act as a kind of stopwatch for photons. Unlike cameras, measuring the spatial distribution of color and intensity, the detector only records how long it takes the photons produced by a split-second pulse of laser light to bounce off each object in any given scene and reach the sensor. The further away an object is, the longer it will take each reflected photon to reach the sensor. The information about the timings of each photon reflected in the scene—what the researchers call the temporal data—is collected in a very simple graph.

Those graphs are then transformed into a 3-D image with the help of a sophisticated neural network algorithm. The researchers trained the algorithm by showing it thousands of conventional photos of the team moving and carrying objects around the lab, alongside temporal data captured by the single-point detector at the same time. Eventually, the network had learned enough about how the temporal data corresponded with the photos that it was capable of creating highly accurate images from the temporal data alone. In the proof-of-principle experiments, the team managed to construct moving images at about 10 frames per second from the temporal data, although the hardware and algorithm used has the potential to produce thousands of images per second. Currently, the neural net's ability to create images is limited to what it has been trained to pick out from the temporal data of scenes created by the researchers. However, with further training and even by using more advanced algorithms, it could learn to visualize a varied range of scenes, widening its potential applications in real-world situations.

Submission + - China Is What Orwell Feared: Using AI to enhance government totalitarian control (theatlantic.com)

Submitted by Anonymous Coward
An anonymous reader writes: Xi Jinping is exporting this technology to regimes around the globe.

Xi’s pronouncements on AI have a sinister edge. Artificial intelligence has applications in nearly every human domain, from the instant translation of spoken language to early viral-outbreak detection. But Xi also wants to use AI’s awesome analytical powers to push China to the cutting edge of surveillance. He wants to build an all-seeing digital system of social control, patrolled by precog algorithms that identify potential dissenters in real time.

China’s government has a history of using major historical events to introduce and embed surveillance measures. In the run-up to the 2008 Olympics in Beijing, Chinese security services achieved a new level of control over the country’s internet. During China’s coronavirus outbreak, Xi’s government leaned hard on private companies in possession of sensitive personal data. Any emergency data-sharing arrangements made behind closed doors during the pandemic could become permanent.

Xi Jinping endorsed this explanation for the Soviet collapse in a 2013 address to party cadres. “Why did the Soviet Union disintegrate?” he asked his audience. “An important reason is that in the ideological domain, competition is fierce!” The party leadership is determined to avoid the Soviet mistake. A leaked internal party directive from 2013 describes “the very real threat of Western anti-China forces and their attempt at carrying out westernization” within China. The directive describes the party as being in the midst of an “intense, ideological struggle” for survival. According to the directive, the ideas that threaten China with “major disorder” include concepts such as “separation of powers,” “independent judiciaries,” “universal human rights,” “Western freedom,” “civil society,” “economic liberalism,” “total privatization,” “freedom of the press,” and “free flow of information on the internet.” To allow the Chinese people to contemplate these concepts would “dismantle [our] party’s social foundation” and jeopardize the party’s aim to build a modern, socialist future.

Related: China’s Plans to Win Control of the Global Order.

Submission + - Spacecraft Made from Ultra Thin Foam Could Reach Proxima Centauri in 185 Years (newsweek.com)

Submitted by Anonymous Coward
An anonymous reader writes: From Newsweek:

A hypothetical spacecraft made from an extremely thin layer of a synthetic foam could technically make it to our closest neighboring star Proxima Centauri in just 185 years, scientists have said. If Voyager were to make the same journey, it would take around 73,000 years, according to NASA ...

Submission + - Attention Rogue Drone Pilots: AI Can See You (ieee.org)

Submitted by schwit1
schwit1 writes: The minute details of rogue drone’s movements in the air may unwittingly reveal the drone pilot’s location—possibly enabling authorities to bring the drone down before, say, it has the opportunity to disrupt air traffic or cause an accident. And it’s possible without requiring expensive arrays of radio triangulation and signal-location antennas.

So says a team of Israeli researchers who have trained an AI drone-tracking algorithm to reveal the drone operator’s whereabouts, with a better than 80 per cent accuracy level. They are now investigating whether the algorithm can also uncover the pilot’s level of expertise and even possibly their identity.

Weiss said his group tested their drone tracking algorithm using Microsoft Research’s open source drone and autonomous vehicle simulatorAirSim. The group presented their work-in-progress at theFourth International Symposiumon Cyber Security, Cryptology and Machine Learning at Ben-Gurion University earlier this month.

Theirpaperboasts a 73 per cent accuracy rate in discovering drone pilots’ locations. Weiss said that in the few weeks since publishing that result, they’ve now improved the accuracy rate to 83 per cent.

Submission + - AI distinguishes birds that even experts can't (sciencemag.org)

Submitted by sciencehabit
sciencehabit writes: It’s a fact of life for birders that some species are fiendishly difficult to tell apart—in particular, the sparrows and drab songbirds dubbed “little brown jobs.” Distinguishing individuals is nearly impossible. Now, a computer program analyzing photos and videos has accomplished that feat. The advance promises to reveal new information on bird behaviors.

The tool, called a convolutional neural network, sifts through thousands of pictures to figure out which visual features can be used to classify a given image; it then uses that information to classify new images. When given photos it hadn’t seen before, the neural network correctly identified individual birds 90% of the time, often better than human experts.

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