The Category5.TV Newsroom

Here are the stories we're following for the week of Wednesday July 25, 2018

According to research published in Nature, machine helps robots perform chemistry experiments faster than human scientists.

According to research published in Nature, machine learning can help robots perform chemistry experiments faster than human scientists.

Researchers have been exploring how algorithms can predict the outcome of chemical reactions for a while now, but this project goes one step further and actually uses a real robot to carry out some of the experiments.

It doesn’t look anything like what you’d imagine. There is no humanoid robot on wheels zipping around a lab, or a mechanical arm swishing beakers of colourful liquid. Rather, it’s a system that contains a series of pumps and reactors all attached to a mass spectrometer, a nuclear magnetic resonance spectrometer, and a infrared spectrometer.

The pumps contain samples of the chemicals to be mixed, the solution is then fed into reactor flasks, and sent to the all the different types of spectrometers to be analysed. It’s nothing too fancy, and most of the hard work is done by the machine learning algorithms behind the robot.

The system determines if a chemical reaction has occurred or not, scoring it as a zero for non-reactive, and one for reactive. The machine studies the information from the different spectrometers to see if new molecules have been forged.

The model was trained on 72 reactive and non-reactive mixtures from known chemical reactions classified by human chemists. A team of researchers from the University of Glasgow built a neural network and trained it on nearly 3,500 reactions. They flagged almost 600 to be held back for validation, and then tested it on nearly 2,000 reactions.

It’s pretty accurate, and can predict if a chemical reaction will take place about 86 percent of the time, according to simulations. After this stage, the robot can then begin performing some of the reactions chosen by the algorithm.

The system saves time and energy by helping chemists discard pointless experiments that probably won’t result in anything useful. It can also give them hints to what reactions they should explore to find new molecules for drugs, dyes, or new materials.

Source: www.theregister.co.uk

Sent to us by: Roy W. Nash

A prolific hacking group has struck again, this time stealing close to $1 million from Russia’s PIR Bank.

A prolific hacking group has struck again, this time stealing close to $1 million from Russia’s PIR Bank.

The heist occurred on July 3rd—about five weeks after the sophisticated hackers first gained access to the bank’s network by compromising a router used by a regional branch.

The theft, which is conservatively estimated at about $910,000 USD, is the latest achievement of a group who is being called the "MoneyTaker" group; named after a piece of malware they commonly use.

While utilizing several sysadmin tools and custom malware, one of the earlier hacks of a Russian bank’s internal network was initiated by gaining access to the home computer of one of its system admins.

First reported last November that members of the hacker group had conducted 20 successful attacks on financial institutions and legal firms in the US, UK, and Russia at that time. In a follow-up, it was reported that MoneyTaker netted about $14 million in the hacks, 16 of which were carried out on US targets, five on Russian banks, and one on a banking-software company in the UK.

Source: arstechnica.com

Sent to us by: Roy W. Nash

Just when we started to think autonomous vehicles were looking good, someone has developed a GPS spoofing device that can make them drive straight into oncoming traffic.

Just when we started to think autonomous vehicles were looking good, someone has developed a GPS spoofing device that can send them driving straight into oncoming traffic.

Billions of people—and a growing number of autonomous vehicles—rely on mobile navigation services from Google, Uber, and others to provide real-time driving directions. A new proof-of-concept attack demonstrates how hackers could inconspicuously steer a targeted automobile to the wrong destination or, worse, endanger passengers by sending them down the wrong way of a one-way road.

The attack starts with a $225 piece of hardware that’s planted in or underneath the targeted vehicle that spoofs the radio signals used by civilian GPS services. It then uses algorithms to plot a fake “ghost route” that mimics the turn-by-turn navigation directions contained in the original route. Depending on the hackers’ ultimate motivations, the attack can be used to divert an emergency vehicle or a specific passenger to an unintended location or to follow an unsafe route.

Researchers responsible for the device are thankfully not out to cause trouble. They're from Virginia Tech, China’s University of Electronic Sciences and Technology, and Microsoft Research. They wanted to demonstrate the vulnerabilities in our current GPS-driven infrastructure. They warned, "The threat becomes more realistic as car makers are adding autopilot features so that human drivers can be less involved (or completely disengaged)."

The researchers propose several countermeasures. The one they say is the most promising in terms of its effectiveness and cost is “computer vision techniques to cross-examine the physical-world landmarks and street signs with digital maps.” Given the widespread use of cameras and LIDAR, this protection could be put in place with software-level upgrades.

Source: arstechnica.com

Sent to us by: Roy W. Nash

If you think hackers are all bad, think again as we look at a hardware hacker who has solved the issue of Amazon's Alexa devices: what if the user can’t speak or hear?

If you think hackers are all bad, think again as we look at a hardware hacker who has solved the issue of Amazon's Alexa devices: what if the user can’t speak or hear?

"If voice is the future of computing, what about those who cannot speak or hear?" That's the question posed by developer Abhishek Singh, the creator of an app that allows Amazon Alexa to respond to sign language.

Singh's project uses a camera-based system to identify gestures and interpret them as text and speech.

The developer says future smart home devices should be designed to be inclusive for deaf users.

The past few years have seen a rise in popularity of voice assistants run by Amazon, Google, and Apple. In fact, a study by the Smart Audio Report suggests adoption of smart speakers has exceeded that of smartphones and tablets in the US. But for the deaf community, a future where devices are increasingly controlled by voice poses many problems.

Speech recognition typically has trouble being able to pick up the rhythms of deaf users. And a lack of hearing presents a clear challenge to communicating with voice-based assistants.

Singh's project offers one potential solution—rigging Amazon's Alexa to respond in text to American Sign Language.

The developer trained an AI using the machine-learning platform Tensorflow, which involved repeatedly gesturing in front of a webcam to teach the system the basics of sign language.

Once the system was able to respond to his hand movements, he connected it to Google's text-to-speech software to read the corresponding words aloud.

The Amazon Echo reacts and its vocal response is automatically transcribed by the computer into text, which is read by the user.

As a solution, it is a workaround, with the laptop as an interpreter between the user and Alexa.

But, as Singh says: "There's no reason that Amazon Show, or any of the camera and screen based voice assistants, couldn't build this functionality right in."

Amazon has taken the hint and announced that, as of Monday, more Alexa users will have the option to turn on captions for Echo devices with a screen.

Alexa Captioning has previously been available for US owners of the Echo Show and Echo Spot. The company is now bringing the feature to users in the UK, as well as Germany, Japan, India, France, Canada, Australia, and New Zealand.

Source: www.bbc.co.uk

Sent to us by: Roy W. Nash