Original image

Watch 24 Hours of Internet Activity Around the World in 8 Seconds

Original image

By Peter Weber

Behold, the internet. In about eight seconds, you can watch a whole day's worth of internet activity around the world, with the higher activity in reds and yellows and the wave shape showing where it's day and night.

The map was put together by an anonymous researcher in a self-styled "Internet Census 2012." Why isn't he or she taking credit for this remarkable feat of cyber-cartography? The data came from infecting 420,000 computers with automated, web-crawling botnets — and "hacking into 420,000 computers is highly illegal," says Adam Clark Estes at Vice.

What are we actually seeing, and how sketchy is its provenance? The researcher, using the 420,000 infected devices, tried to figure out how many of the world's 3.6 billion IPv4 (Internet Protocol version 4) addresses are active; roughly speaking, he got responses from 1.2 billion devices around the world. The map shows the average usage of each device each half hour.

The map isn't totally comprehensive: His botnet, called Carna (after "the Roman goddess for the protection of inner organs and health"), only infected Linux-based devices with some user name–password combination of "root," "admin," or nothing. Also, the world is slowly switching to IPv6, and Carna doesn't measure those devices — in fact, he says, "with a growing number of IPv6 hosts on the internet, 2012 may have been the last time a census like this was possible." At the same time, "this looks pretty accurate," HD Moore, who used ethical and legal means to conduct a similar survey of smaller scope but larger timeframe, tells Ars Technica.

That said, it's a snapshot of 2012, with a limited shelf life. "With cheap smartphones taking off in Africa and $20 tablets popping up in India, the world is becoming more connected by the minute," says Vice's Estes. "So in a few years' time that confetti-colored map of the world above will look less like a chart of privilege and more like an acid trip of progress."

As for the ethics of this census, let's call it "interesting, amoral, and illegal," says Infosecurity Magazine.

The [botnet] binaries he developed and deployed — it's difficult to call them malware since they had no mal-intent; but it's difficult not to call them malware since they were installed without invitation — were designed to do no harm, to run at the lowest possible priority, and included a watchdog to self-destruct if anything went wrong. He also included a readme file with "a contact email address to provide feedback for security researchers, ISPs and law enforcement who may notice the project." [Infosecurity]

And if we're being charitable, you could argue that he performed a public service by highlighting how poorly protected our computers, routers, and other internet-connected devices are. Here's a "crude physical analogy" for what the researcher did, says Michael Lee atZDNet: By himself, he would have been like "a burglar who walks from house to house in a neighborhood, checking to see whether anyone has forgotten to put a lock on their door."

With an opportunistic attack, given enough "neighborhoods" and enough time, one could potentially gain an insight into how poorly protected people are. However, with the burglar being a single person, doing so would take them a prohibitively long time — unless, theoretically, they were able to recruit vulnerable households and send them to different neighborhoods to do the same.... The Carna botnet... highlighted just how many people left their metaphorical front doors unlocked by using default passwords and user logins. [ZDNet]

Still, if this researcher were caught in the U.S., he'd "likely be slapped with one violation of the Computer Fraud and Abuse Act for every computer breached and face something like 50 consecutive life sentences for the sum total," says Vice's Estes. "I'm being sightly facetious here but only slightly." So why take that risk? To see if it could be done, basically.

Building and running a gigantic botnet and then watching it as it scans nothing less than the whole internet at rates of billions of IPs per hour over and over again is really as much fun as it sounds like. I did not want to ask myself for the rest of my life how much fun it could have been or if the infrastructure I imagined in my head would have worked as expected. I saw the chance to really work on an internet scale, command hundred thousands of devices with a click of my mouse, portscan and map the whole internet in a way nobody had done before, basically have fun with computers and the internet in a way very few people ever will. I decided it would be worth my time. [Internet Census 2012]

More from The Week...

6 Adorable Baby Animals Standing Up for the First Time


Should Google Glass be Banned from the Road?


7 Words Guaranteed to Make You a Better Writer

Original image
iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

Original image
Stephen Missal
New Evidence Emerges in Norway’s Most Famous Unsolved Murder Case
May 22, 2017
Original image
A 2016 sketch by a forensic artist of the Isdal Woman
Stephen Missal

For almost 50 years, Norwegian investigators have been baffled by the case of the “Isdal Woman,” whose burned corpse was found in a valley outside the city of Bergen in 1970. Most of her face and hair had been burned off and the labels in her clothes had been removed. The police investigation eventually led to a pair of suitcases stuffed with wigs and the discovery that the woman had stayed at numerous hotels around Norway under different aliases. Still, the police eventually ruled it a suicide.

Almost five decades later, the Norwegian public broadcaster NRK has launched a new investigation into the case, working with police to help track down her identity. And it is already yielding results. The BBC reports that forensic analysis of the woman’s teeth show that she was from a region along the French-German border.

In 1970, hikers discovered the Isdal Woman’s body, burned and lying on a remote slope surrounded by an umbrella, melted plastic bottles, what may have been a passport cover, and more. Her clothes and possessions were scraped clean of any kind of identifying marks or labels. Later, the police found that she left two suitcases at the Bergen train station, containing sunglasses with her fingerprints on the lenses, a hairbrush, a prescription bottle of eczema cream, several wigs, and glasses with clear lenses. Again, all labels and other identifying marks had been removed, even from the prescription cream. A notepad found inside was filled with handwritten letters that looked like a code. A shopping bag led police to a shoe store, where, finally, an employee remembered selling rubber boots just like the ones found on the woman’s body.

Eventually, the police discovered that she had stayed in different hotels all over the country under different names, which would have required passports under several different aliases. This strongly suggests that she was a spy. Though she was both burned alive and had a stomach full of undigested sleeping pills, the police eventually ruled the death a suicide, unable to track down any evidence that they could tie to her murder.

But some of the forensic data that can help solve her case still exists. The Isdal Woman’s jaw was preserved in a forensic archive, allowing researchers from the University of Canberra in Australia to use isotopic analysis to figure out where she came from, based on the chemical traces left on her teeth while she was growing up. It’s the first time this technique has been used in a Norwegian criminal investigation.

The isotopic analysis was so effective that the researchers can tell that she probably grew up in eastern or central Europe, then moved west toward France during her adolescence, possibly just before or during World War II. Previous studies of her handwriting have indicated that she learned to write in France or in another French-speaking country.

Narrowing down the woman’s origins to such a specific region could help find someone who knew her, or reports of missing women who matched her description. The case is still a long way from solved, but the search is now much narrower than it had been in the mystery's long history.

[h/t BBC]