Build A Fungus Foraging App With Machine Learning

August 22, 2019 by Pat Whetman 42 Comments

As the 2019 mushroom foraging season approaches it’s timely to combine my thirst for knowledge about low level machine learning (ML) with a popular pastime that we enjoy here where I live. Just for the record, I’m not an expert on ML, and I’m simply inviting readers to follow me back down some rabbit holes that I recently explored.

But mushrooms, I do know a little bit about, so firstly, a bit about health and safety:

The app created should be used with extreme caution and results always confirmed by a fungus expert.
Always test the fungus by initially only eating a very small piece and waiting for several hours to check there is no ill effect.
Always wear gloves – It’s surprisingly easy to absorb toxins through fingers.

Since this is very much an introduction to ML, there won’t be too much terminology and the emphasis will be on having fun rather than going on a deep dive. The system that I stumbled upon is called XGBoost (XGB). One of the XGB demos is for binary classification, and the data was drawn from The Audubon Society Field Guide to North American Mushrooms. Binary means that the app spits out a probability of ‘yes’ or ‘no’ and in this case it tends to give about 95% probability that a common edible mushroom (Agaricus campestris) is actually edible.

The app asks the user 22 questions about their specimen and collates the data inputted as a series of letters separated by commas. At the end of the questionnaire, this data line is written to a file called ‘fungusFile.data’ for further processing.

XGB can not accept letters as data so they have to be mapped into ‘classic LibSVM format’ which looks like this: ‘3:218’, for each letter. Next, this XGB friendly data is split into two parts for training a model and then subsequently testing that model.

Installing XGB is relatively easy compared to higher level deep learning systems and runs well on both Linux Ubuntu 16.04 and on a Raspberry Pi. I wrote the deployment app in bash so there should not be any additional software to install. Before getting any deeper into the ML side of things, I highly advise installing XGB, running the app, and having a bit of a play with it.

Training and testing is carried out by running bash runexp.sh in the terminal and it takes less than one second to process the 8124 lines of fungal data. At the end, bash spits out a set of statistics to represent the accuracy of the training and also attempts to ‘draw’ the decision tree that XGB has devised. If we have a quick look in directory ~/xgboost/demo/binary_classification, there should now be a 0002.model file in it ready for deployment with the questionnaire.

I was interested to explore the decision tree a bit further and look at the way XGB weighted different characteristics of the fungi. I eventually got some rough visualisations working on a Python based Jupyter Notebook script:

Obviously this app is not going to win any Kaggle competitions since the various parameters within the software need to be carefully tuned with the help of all the different software tools available. A good place to start is to tweak the maximum depth of the tree and the number or trees used. Depth = 4 and number = 4 seems to work well for this data. Other parameters include the feature importance type, for example: gain, weight, cover, total_gain or total_cover. These can be tuned using tools such as SHAP.

Finally, this app could easily be adapted to other questionnaire based systems such as diagnosing a particular disease, or deciding whether to buy a particular stock or share in the market place.

An even more basic introduction to ML goes into the baseline theory in a bit more detail – well worth a quick look.

Looking Around Corners With F-K Migration

August 22, 2019 by Maya Posch 10 Comments

The concept behind non-line-of-sight (NLOS) imaging seems fairly easy to grasp: a laser bounces photons off a surface that illuminate objects that are within in sight of that surface, but not of the imaging equipment. The photons that are then reflected or refracted by the hidden object make their way back to the laser’s location, where they are captured and processed to form an image. Essentially this allows one to use any surface as a mirror to look around corners.

Main disadvantage with this method has been the low resolution and high susceptibility to noise. This led a team at Stanford University to experiment with ways to improve this. As detailed in an interview by Tech Briefs with graduate student [David Lindell], a major improvement came from an ultra-fast shutter solution that blocks out most of the photons that return from the wall that is being illuminated, preventing the photons reflected by the object from getting drowned out by this noise.

The key to getting the imaging quality desired, including with glossy and otherwise hard to image objects, was this f-k migration algorithm. As explained in the video that is embedded after the break, they took a look at what methods are used in the field of seismology, where vibrations are used to image what is inside the Earth’s crust, as well as synthetic aperture radar and similar. The resulting algorithm uses a sequence of Fourier transformation, spectrum resampling and interpolation, and the inverse Fourier transform to process the received data into a usable image.

This is not a new topic; we covered a simple implementation of this all the way back in 2011, as well as a project by UK researchers in 2015. This new research shows obvious improvements, making this kind of technology ever more viable for practical applications.

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Largest Chip Ever Holds 1.2 Trillion Transistors

August 21, 2019 by Al Williams 49 Comments

We get it, press releases are full of hyperbole. Cerebras recently announced they’ve built the largest chip ever. The chip has 400,000 cores and contains 1.2 trillion transistors on a die over 46,000 square mm in area. That’s roughly the same as a square about 8.5 inches on each side. But honestly, the WSE — Wafer Scale Engine — is just most of a wafer not cut up. Typically a wafer will have lots of copies of a device on it and it gets split into pieces.

According to the company, the WSE is 56 times larger than the largest GPU on the market. The chip boasts 18 gigabytes of storage spread around the massive die. The problem isn’t making such a beast — although a normal wafer is allowed to have a certain number of bad spots. The real problems come through things such as interconnections and thermal management.

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Russian Robot To Visit Space Station

August 21, 2019 by Al Williams 23 Comments

The Russians were the first to send a dog into space, the first to send a man, and the first to send a woman. However, NASA sent the first humanoid robot to the International Space Station. The Russians, though, want to send FEDOR and proclaim that while Robonaut flew as cargo, a FEDOR model — Skybot F-850 — will fly the upcoming MS-14 supply mission as crew.

Defining the term robot can be tricky, with some thinking a proper robot needs to be autonomous and others seeing robotics under human control as enough. The Russian FEDOR robot is — we think — primarily a telepresence device, but it remains an impressive technical achievement. The press release claims that it can balance itself and do other autonomous actions, but it appears that to do anything tricky probably requires an operator. You can see the robot in ground tests at about the one minute mark in the video below.

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An (Almost) Free Apollo-Era Rocket

August 16, 2019 by Al Williams 10 Comments

According to recent news reports, NASA’s Marshall Space Flight Center in Huntsville Alabama wants to give away a piece of history — an engineering test article of a Saturn I Block I booster. The catch? You’ll need to pay to haul it off, which will cost about $250,000. According to C|Net, the offer appears to be for museums and schools, but it’s likely that price tag would probably scare most private buyers off anyway.

On the other hand, if you are a museum, library, school, or university, you can score cheap or free NASA stuff using their GSAXcess portal. In general, you do have to pay shipping. For example, a flexible thermal blanket from the shuttle costs $37.28. A heat tile runs about $25.

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This Week In Security: Black Hat, DEF CON, And Patch Tuesday

August 16, 2019 by Jonathan Bennett 11 Comments

Blackhat and DEF CON both just wrapped, and Patch Tuesday was this week. We have a bunch of stories to cover today.

First some light-hearted shenanigans. Obviously inspired by Little Bobby Tables, Droogie applied for the vanity plate “NULL”. A year went by without any problems, but soon enough it was time to renew his registration. The online registration form refused to acknowledge “NULL” as a valid license plate. The hilarity didn’t really start until he got a parking ticket, and received a bill for $12,000. It seems that the California parking ticket collection system can’t properly differentiate between “NULL” and a null value, and so every ticket without a license plate is now unintentionally linked to his plate.

In the comments on the Ars Technica article, it was suggested that “NULL” simply be added to the list of disallowed vanity plates. A savvy reader pointed out that the system that tracks disallowed plates would probably similarly choke on a “NULL” value.

Hacking an F-15

In a surprising move, Air Force officials brought samples of the Trusted Aircraft Information Download Station (TADS) from an F-15 to DEF CON. Researchers were apparently able to compromise those devices in a myriad of ways. This is a radical departure from the security-through-obscurity approach that has characterized the U.S. military for years.

Next year’s DEF CON involvement promises to be even better as the Air Force plans to bring researchers out to an actual aircraft, inviting them to compromise it in every way imaginable.

Patch Tuesday

Microsoft’s monthly dump of Windows security fixes landed this week, and it was a doozy. First up are a pair of remotely exploitable Remote Desktop vulnerabilities, CVE-2019-1222 and CVE-2019-1226. It’s been theorized that these bugs were found as part of an RDP code review launched in response to the BlueKeep vulnerability from earlier this year. The important difference here is that these bugs affect multiple versions of Windows, up to and including Windows 10.

What the CTF

Remember Tavis Ormandy and his Notepad attack? We finally have the rest of the story! Go read the whole thing, it’s a great tale of finding something strange, and then pulling it apart looking for vulnerabilities.

Microsoft Windows has a module, MSCTF, that is part of the Text Services Framework. What does the CTF acronym even stand for? That’s not clear. It seems that CTF is responsible for handling keyboard layouts, and translating keystrokes based on what keyboard type is selected. What is also clear is that every time an application builds a window, that application also connects to a CTF process. CTF has been a part of Microsoft’s code base since at least 2001, with relatively few code changes since then.

CTF doesn’t do any validation, so an attacker can connect to the CTF service and claim to be any process. Tavis discovered he could effectively attempt to call arbitrary function pointers of any program talking to the same CTF service. Due to some additional security measures built into modern Windows, the path to an actual compromise is rather convoluted, but by the end of the day, any CFT client can be compromised, including notepad.

The most interesting CFT client Tavis found was the login screen. The exploit he demos as part of the write-up is to lock the computer, and then compromise the login in order to spawn a process with system privileges.

The presence of this unknown service running on every Windows machine is just another reminder that operating systems should be open source.

Biostar 2

Biostar 2 is a centralized biometric access control system in use by thousands of organizations and many countries around the globe. A pair of Israeli security researchers discovered that the central database that controls the entire system was unencrypted and unsecured. 23 Gigabytes of security data was available, including over a million fingerprints. This data was stored in the clear, rather than properly hashed, so passwords and fingerprints were directly leaked as a result. This data seems to have been made available through an Elasticsearch instance that was directly exposed to the internet, and was found through port scanning.

If you have any exposure to Biostar 2 systems, you need to assume your data has been compromised. While passwords can be changed, fingerprints are forever. As biometric authentication becomes more widespread, this is an unexplored side effect.

Locating Targets With Charm Courtesy Of A Life Size Portal Turret

August 12, 2019 by Maya Posch 6 Comments

What better way to count down the last 7 weeks to a big hacker camp like SHA2017 than by embarking on a last-minute, frantic build? That was [Yvo]’s thought when he decided to make a life-sized version of the adorably lethal turrets from the Valve’s Portal video games. Since that build made it to the finish line back then with not all features added, he finished it up for the CCC camp 2019 event, including the ability to close, open, target and shoot Nerf darts.

Originally based on the miniature 2014 turret (covered on Hackaday as well), [Yvo] details this new project in a first and second work log, along with a detailed explanation of how it all goes together and works. While the 2017 version took a mere 50 days to put together, the whole project took about 300 hours of 3D printing. It also comes with four Nerf guns which use flywheels to launch the darts. The wheels are powered using quadcopter outrunner motors that spin at 25,000 RPM. The theoretical speed of a launched dart is over 100km/h, with 18 darts per gun and a fire rate of 2 darts per second.

The basic movement control for the system is handled by an Arduino Mega, while the talking and vision aspects are taken care of by a Raspberry Pi 3+, which ultimately also makes the decisions about how to move the system. As one can see in the video after the link, the system seems to work pretty well, with a negligible number of fatalities among company employees.

Though decidedly not a project for the inexperienced tinkerer, [Yvo] has made all of the design files available along with the software. We’re still dubious about the claims about the promised cake for completing one of these turrets, however.

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