Monthly Archives: March 2018

Facebook Acknowledges It Has Been Keeping Records of Android Users’ Calls, Texts

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Last week, a user found that Facebook had a record of the date, time, duration, and recipient of calls he had made from the past few years. A couple days later, Ars Technica published an account of several others — all Android users — who found similar records. Now, Slate Magazine is reporting that Facebook has acknowledged that it was collecting and storing these logs, “attributing it to an opt-in feature for those using Messenger or Facebook Lite on an Android device.” The company did however deny that it was collecting call or text history without a user’s permission. From the report: “This helps you find and stay connected with the people you care about, and provides you with a better experience across Facebook,” the company said in a post Sunday. “People have to expressly agree to use this feature. We introduced this feature for Android users a couple of years ago. Contact importers are fairly common among social apps and services as a way to more easily find the people you want to connect with.”

Ars Technica refuted their claim that everyone knowingly opted in. Instead, Ars Technica’s Sean Gallagher claimed, that opt-in was the default setting and users were not separately alerted to it. Nor did Facebook ever say publicly that it was collecting that information. “Facebook says that the company keeps the data secure and does not sell it to third parties,” Gallagher wrote. “But the post doesn’t address why it would be necessary to retain not just the numbers of contacts from phone calls and SMS messages, but the date, time, and length of those calls for years.”

Source: Facebook Acknowledges It Has Been Keeping Records of Android Users’ Calls, Texts – Slashdot

New Slack Tool Lets Your Boss Potentially Access Far More of Your Data Than Before, without notification

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According to Slack’s new guidelines, however, Compliance Exports will be replaced by “a self-service export tool” on April 20th. Previously, an employer had to request a data dump of all communications to get access to private channels and direct messages. This new tool should streamline things so they can archive all your shit-talk and time-wasting with colleagues on a regular basis. The tool not only makes it easy for an admin to access everything with a few clicks, it also enables automatic exports to be scheduled on a daily, weekly, or monthly basis. An employer still has to go through a request process to get the tool, but Slack declined to elaborate on what’s involved in that process.

What’s particularly concerning is that Compliance Exports were designed so they notified users when they were enabled, and future exports only covered data that was generated after that notification. A spokesperson for Slack confirmed to Gizmodo that this won’t be the case going forward. The new tool will be able to export all of the data that your Slack settings previously retained. Whereas before, if you were up on Slack policy, you could feel pretty comfortable that your private conversations were private unless you got that Compliance Exports notification. After the notification, you’d want to make sure you didn’t discuss potentially sensitive topics in Slack. Now, anyone who was under the impression that they were relatively safe might have some cause to worry.

Source: New Slack Tool Lets Your Boss Potentially Access Far More of Your Data Than Before

2 + 2 = 4, er, 4.1, no, 4.3… Nvidia’s Titan V GPUs spit out ‘wrong answers’ in scientific simulations

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Nvidia’s flagship Titan V graphics cards may have hardware gremlins causing them to spit out different answers to repeated complex calculations under certain conditions, according to computer scientists.

The Titan V is the Silicon Valley giant’s most powerful GPU board available to date, and is built on Nv’s Volta technology. Gamers and casual users will not notice any errors or issues, however folks running intensive scientific software may encounter occasional glitches.

One engineer told The Register that when he tried to run identical simulations of an interaction between a protein and enzyme on Nvidia’s Titan V cards, the results varied. After repeated tests on four of the top-of-the-line GPUs, he found two gave numerical errors about 10 per cent of the time. These tests should produce the same output values each time again and again. On previous generations of Nvidia hardware, that generally was the case. On the Titan V, not so, we’re told.

We have repeatedly asked Nvidia for an explanation, and spokespeople have declined to comment. With Nvidia kicking off its GPU Technology Conference in San Jose, California, next week, perhaps then we’ll get some answers.

All in all, it is bad news for boffins as reproducibility is essential to scientific research. When running a physics simulation, any changes from one run to another should be down to interactions within the virtual world, not rare glitches in the underlying hardware.

[…]

Unlike previous GeForce and Titan GPUs, the Titan V is geared not so much for gamers but for handling intensive parallel computing workloads for data science, modeling, and machine learning.

And at $2,999 (£2,200) a pop, it’s not cheap to waste resources and research time on faulty hardware. Engineers speaking to The Register on condition of anonymity to avoid repercussions from Nvidia said the best solution to these problems is to avoid using Titan V altogether until a software patch has been released to address the mathematical oddities.

Source: 2 + 2 = 4, er, 4.1, no, 4.3… Nvidia’s Titan V GPUs spit out ‘wrong answers’ in scientific simulations • The Register

This kind of reminds me of when Intel brought out the Pentium. They couldn’t count either.

Siri Can Expose Your Hidden Notifications Even When Your Phone Is Locked

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With iOS 11, Apple added a new setting that lets you choose whether you want previews of your notifications to appear on your lock screen. By default, iOS shows a preview of your notifications only when your phone is unlocked, via some form of authentication like Face ID. But Siri will read your notifications from third-party apps aloud even if your phone is locked. This means anyone with physical access to your phone could hear messages meant just for you. MacMagazine first reported the issue after one of its readers noticed the peculiar behavior.

We tested the issue with some texts and Facebook Messenger exchanges. When my partner pressed the iPhone’s side button and asked Siri to “read my notifications,” the snitch of a voice assistant read the contents of my Facebook Messenger notifications aloud.

However, notifications from Apple’s own Messages app remained properly hidden behind the locked screen, leaving my texts secure. If you ask Siri to read your messages from Apple’s app aloud, you’ll be greeted by Siri telling you to unlock your iPhone if you want those juicy deets.

We’ve reached out to Apple for comment.

Notification contents in iOS 11 are hidden on locked devices by default. With an iPhone X, that means you can look at your phone (or tap the fingerprint sensor on other iOS devices) and watch the contents of your notifications appear. You can edit the option by visiting Settings > Notifications and toggling between the “Always,” “Never,” and “When Unlocked” options, although changing the setting to “Never” does not appear to address the issue. For now, your best bet may simply be to only allow Siri to be activated when your phone is unlocked.

Source: Siri Can Expose Your Hidden Notifications Even When Your Phone Is Locked [Updated]

IBM claims its machine learning library is 46x faster than TensorFlow • The Register

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Analysis IBM boasts that machine learning is not just quicker on its POWER servers than on TensorFlow in the Google Cloud, it’s 46 times quicker.

Back in February Google software engineer Andreas Sterbenz wrote about using Google Cloud Machine Learning and TensorFlow on click prediction for large-scale advertising and recommendation scenarios.

He trained a model to predict display ad clicks on Criteo Labs clicks logs, which are over 1TB in size and contain feature values and click feedback from millions of display ads.

Data pre-processing (60 minutes) was followed by the actual learning, using 60 worker machines and 29 parameter machines for training. The model took 70 minutes to train, with an evaluation loss of 0.1293. We understand this is a rough indicator of result accuracy.

Sterbenz then used different modelling techniques to get better results, reducing the evaluation loss, which all took longer, eventually using a deep neural network with three epochs (a measure of the number of times all of the training vectors are used once to update the weights), which took 78 hours.

[…]

Thomas Parnell and Celestine Dünner at IBM Research in Zurich used the same source data – Criteo Terabyte Click Logs, with 4.2 billion training examples and 1 million features – and the same ML model, logistic regression, but a different ML library. It’s called Snap Machine Learning.

They ran their session using Snap ML running on four Power System AC922 servers, meaning eight POWER9 CPUs and 16 Nvidia Tesla V100 GPUs. Instead of taking 70 minutes, it completed in 91.5 seconds, 46 times faster.

They prepared a chart showing their Snap ML, the Google TensorFlow and three other results:

IBM_Snap_ML_chart

A 46x speed improvement over TensorFlow is not to be sneezed at. What did they attribute it to?

They say Snap ML features several hierarchical levels of parallelism to partition the workload among different nodes in a cluster, takes advantage of accelerator units, and exploits multi-core parallelism on the individual compute units

  1. First, data is distributed across the individual worker nodes in the cluster
  2. On a node data is split between the host CPU and the accelerating GPUs with CPUs and GPUs operating in parallel
  3. Data is sent to the multiple cores in a GPU and the CPU workload is multi-threaded

Snap ML has nested hierarchical algorithmic features to take advantage of these three levels of parallelism.

Source: IBM claims its machine learning library is 46x faster than TensorFlow • The Register

22 Ambassadors Recommend the One Book to Read Before Visiting Their Country

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Preparing for a visit to a foreign country can often be overwhelming, with no shortage of things to learn before you go. Where should you eat? Where should you stay? What do you tip? More so than this service information, though, is a sense of cultural understanding that’s hard to put your finger on. With this in mind, language learning app Babbel asked foreign ambassadors to the U.S. to pick the book they believe first-time visitors to their country should read before they arrive. Their answers may surprise you.

Source: 22 Ambassadors Recommend the One Book to Read Before Visiting Their Co – Condé Nast Traveler

The Hilarious (and Terrifying?) Ways Algorithms Have Outsmarted Their Creators

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. As research into AI grows ever more ambitious and complex, these robot brains will challenge the fundamental assumptions of how we humans do things. And, as ever, the only true law of robotics is that computers will always do literally, exactly what you tell them to.

A paper recently published to ArXiv highlights just a handful of incredible and slightly terrifying ways that algorithms think. These AI were designed to reflect evolution by simulating generations while other competing algorithms conquered problems posed by their human masters with strange, uncanny, and brilliant solutions.

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities covers some 27 anecdotes from various computer science projects and is worth a read on its own, but here are a few highlights:

  • A study designed to evolve moving creatures generated ‘hackers’ that would break their simulation by clipping into the ground and using the “free energy” of the simulation’s correction to speed towards their goal.
  • An AI project which pit programs against each other in games of five-in-a-row Tic-Tac-Toe on an infinitely expansive board surfaced the extremely successful method of requesting moves involving extremely long memory addresses which would crash the opponent’s computer and award a win by default.
  • A program designed to simulate efficient ways of braking an aircraft as it landed on an aircraft carrier learned that by maximizing the force on landing—the opposite of its actual goal—the variable holding that value would overflow and flip to zero, creating a practically catastrophic, but technically perfect solution.
  • A test that challenged a simulated robot to walk without allowing its feet to touch the ground saw the robot flip on its back and walk on its elbows (or knees?) as shown in the tweet above.
  • A study to evolve a simulated creature that could jump as high as possible yielded top-heavy creatures on tiny poles that would fall over and spin in mid-air for a technically high ‘jump.’

While the most amusing examples are clearly ones where algorithms abused bugs in their simulations (essentially glitches in the Matrix that gave them superpowers), the paper outlines some surprising solutions that could have practical benefits as well. One algorithm invented a spinning-type movement for robots which would minimize negative effect of inconsistent hardware between bots, for instance.

As the paper notes in its discussion—and you may already be thinking—these amusing stories also reflect the potential for evolutionary algorithms or neural networks to stumble upon solutions to problems that are outside-the-box in dangerous ways. They’re a funnier version of the classic AI nightmare where computers tasked with creating peace on Earth decide the most efficient solution is to exterminate the human race.

The solution, the paper suggests, is not fear but careful experimentation. As humans gain more experience in training these sorts of algorithms, and tweaking along the way, experts gain a better sense of intuition. Still, as these anecdotes prove, it’s basically impossible to avoid unexpected results. The key is to be prepared—and to not hand over the nuclear arsenal to a robot for its very first test.

Source: The Hilarious (and Terrifying?) Ways Algorithms Have Outsmarted Their Creators

AI software that can reproduce like a living thing? Yup, boffins have only gone and done it • The Register

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A pair of computer scientists have created a neural network that can self-replicate.

“Self-replication is a key aspect of biological life that has been largely overlooked in Artificial Intelligence systems,” they argue in a paper popped onto arXiv this month.

It’s an important process in reproduction for living things, and is an important step for evolution through natural selection. Oscar Chang, first author of the paper and a PhD student at Columbia University, explained to The Register that the goal was to see if AI could be made to be continually self improving by mimicking the biological self-replication process.

“The primary motivation here is that AI agents are powered by deep learning, and a self-replication mechanism allows for Darwinian natural selection to occur, so a population of AI agents can improve themselves simply through natural selection – just like in nature – if there was a self-replication mechanism for neural networks.”

The researchers compare their work to quines, a type of computer program that learns to produces copies of its source code. In neural networks, however, instead of the source code it’s the weights – which determine the connections between the different neurons – that are being cloned.

The researchers set up a “vanilla quine” network, a feed-forward system that produces its own weights as outputs. The vanilla quine network can also be used to self-replicate its weights and solve a task. They decided to use it for image classification on the MNIST dataset, where computers have to identify the correct digit from a set of handwritten numbers from zero to nine.

[…]

The test network required 60,000 MNIST images for training, another 10,000 for testing. And after 30 runs, the quine network had an accuracy rate of 90.41 per cent. It’s not a bad start, but its performance doesn’t really compare to larger, more sophisticated image recognition models out there.

The paper states that the “self-replication occupies a significant portion of the neural network’s capacity.” In other words, the neural network cannot focus on the image recognition task if it also has to self-replicate.

“This is an interesting finding: it is more difficult for a network that has increased its specialization at a particular task to self-replicate. This suggests that the two objectives are at odds with each other,” the paper said.

Chang explained he wasn’t sure why this happened, but it’s what happens in nature too.

Source: AI software that can reproduce like a living thing? Yup, boffins have only gone and done it • The Register

SpaceX blasted massive plasma hole in Earth’s ionosphere

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A SpaceX rocket ripped a humongous hole in Earth’s ionosphere during a launch in California last year and may have impaired GPS satellites.

The Falcon 9 rocket was blasted from Vandenberg Air Force Base on 24 August last year. It was carrying the Formosat-5, an Earth observation satellite, built by the Taiwan’s National Space Organization.

As the rocket reached supersonic speeds minutes after liftoff, it sent gigantic circular shock acoustic waves (SAWs) rippling through the atmosphere. These SAWs continued to extend outwards for about 20 minutes at a whopping speed of about 629 to 726 meters per second – equivalent between 0.021 and 0.0242 per cent of the maximum velocity of a sheep in a vacuum in Reg units.

It’s the largest rocket-induced SAW on record, according to a paper published in the Advancing Earth and Space Science journal. The plume tore a gigantic hole, approximately 900 kilometers (559 miles) in diameter stretching to 1,770,000 square kilometers (1,099,827 square miles), more than four times the total area of California.

The ionosphere is a region of the Earth’s upper atmosphere that contains a soup of particles that have been ionized from the Sun’s rays. The researchers estimate that the SAW blasted electrons away, causing the total electron content – the concentration of electrons along a one-meter squared region – to deplete by as much as 70 per cent.

The researchers reckon the fluctuations were probably pretty small and could have led to a range of errors in GPS navigation of up to a meter – not significant enough to cause major problems until the SAW dissipated.

The particularly large circular size of the shock wave was down to the way the Falcon 9 rocket flew. It had a nearly vertical trajectory, compared to most satellite launches that fly over a horizontal trajectory before the satellites are booted into orbit.

Disruptions in the ionosphere are to be expected for every rocket launch and are also detected during volcano blasts and solar flares.

“Understanding how the rocket launches affect our upper atmosphere and space environment is important as these anthropogenic space weather events are expected to increase at an enormous rate in the near future,” the paper concluded.

Source: SpaceX blasted massive plasma hole in Earth’s ionosphere • The Register

‘R2D2’ stops disk-wipe malware before it executes evil commands

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Purdue University researchers reckon they’ve cracked how to protect data against “disk-wipe” malware.

Led by Christopher Gutierrez, the team has created a shim of software that analyses write buffers before they reach storage, and if the write is destructive, it steps in to preserve the data targeted for destruction.

Dubbed R2D2 – “Reactive Redundancy for Data Destruction Protection” – their work will be published in the May issue of the journal Computers & Security.

In this [PDF] pre-press version of the paper, the researchers explained their technique. The inspection is implemented in the virtual machine monitor (VMM) using virtual machine introspection (VMI).

“This has the benefit that it does not rely on the entire OS as a root of trust”, they wrote, and they claimed a latency penalty of between 1 and 4 per cent for batch tasks, and 9 to 20 per cent for interactive tasks.

'R2D2' architecture

Click to enlarge

The system has been tested against various secure delete tools and malware like Shamoon and Stonedrill, and they claim complete success against “all the wiper malware samples in the wild that we experimented with”.

R2D2 intercepts the open file and write file system calls on a guest VM. When it detects an open file request, it checks “all open system calls” to see if the file is already open for writing.

“If the system call requests a write permission, a policy determines if the file should be protected based on a blacklist or whitelist,” they wrote.

Whitelisted files are those not protected; if a blacklisted file is requested, “If the file is on the blacklist, we take a snapshot of the file system because the file is considered critical to system stability.”

If the attacker tries to open a file on neither list, “R2D2 takes a temporary checkpoint of the file system, and subsequent write system calls are analysed, according to analysis policy, to determine if the write is suspect”.

Source: ‘R2D2’ stops disk-wipe malware before it executes evil commands • The Register

How to Find Out Everything Facebook Knows About You

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If you can’t bring yourself to delete your Facebook account entirely, you’re probably thinking about sharing a lot less private information on the site. The company actually makes it pretty easy to find out how much data it’s collected from you, but the results might be a little scary.

When software developer Dylan McKay went and downloaded all of his data from Facebook, he was shocked to find that the social network had timestamps on every phone call and SMS message he made in the past few years, even though he says doesn’t use the app for calls or texts. It even created a log of every call between McKay and his partner’s mom.

To get your own data dump, head to your Facebook Settings and click on “Download a copy of your data” at the bottom of the page. Facebook needs a little time to compile all that information, but it should be ready in about 10 minutes based on my own experience. You’ll receive a notification sending you to a page where you can download the data—after re-entering your account password, of course.

The (likely huge) file downloads onto your computer as a ZIP. Once you extract it, open the new folder and click on the “index.html” to view the data in your browser.

Be sure to check out the Contact Info tab for a list of everyone you’ve ever known and their phone number (creepy, Facebook). You can also scroll down to the bottom of the Friends tab so see what phase of your life Facebook thinks you’re in —I got “Starting Adult Life.”

Source: How to Find Out Everything Facebook Knows About You

IBM unveils ‘world’s smallest computer’ with blockchain at Think 2018

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March 19 is the first day of IBM Think 2018, the company’s flagship conference, where the company will unveil what it claims is the world’s smallest computer. They’re not kidding: It’s literally smaller than a grain of salt.

But don’t let the size fool you: This sucker has the computing power of the x86 chip from 1990. Okay, so that’s not great compared to what we have today, but cut it some slack — you need a microscope to see it.

The computer will cost less than ten cents to manufacture, and will also pack “several hundred thousand transistors,” according to the company. These will allow it to “monitor, analyze, communicate, and even act on data.”

[…]

According to IBM, this is only the beginning. “Within the next five years, cryptographic anchors — such as ink dots or tiny computers smaller than a grain of salt — will be embedded in everyday objects and devices,” says IBM head of research Arvind Krishna. If he’s correct, we’ll see way more of these tiny systems in objects and devices in the years to come.

Source: IBM unveils ‘world’s smallest computer’ with blockchain at Think 2018

A diagram from IBM of the world's smallest computer.

US cops go all Minority Report: Google told to cough up info on anyone near a crime scene

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Efforts to track down criminals in the US state of North Carolina have laid bare a dangerous gap in the law over the use of location data.

Raleigh police went to court at least three times last year and got a warrant requiring Google to share the details of any users that were close to crime scenes during specific times and dates.

The first crime was the murder of a cab driver in November 2016, the second an arson attack in March 2017 and the third, sexual battery, in August 2017 – suggesting that the police force is using the approach to discover potentially incriminating evidence for increasingly less serious crimes.

In each case, the cops used GPS coordinates to draw a rough rectangle around the areas of interest – covering nearly 20 acres in the murder case – and asked for the details of any users that entered those areas in time periods of between 60 to 90 minutes e.g. between 1800 and 1930.

The warrants were granted by a judge complete with an order to prevent disclosure so Google was legally prevented from informing impacted users that their details had been shared with law enforcement. Google complied with the warrants.

It is worth noting that the data haul is not limited to users of Google hardware i.e. phones running Android but also any phone that ran Google apps – which encompasses everything from its driving app service to its calendar, browser, predictive keyboard and so on.

Source: US cops go all Minority Report: Google told to cough up info on anyone near a crime scene • The Register

Over investigation seems like a real breach of privacy to me. That Google collects this information in a fashion that it can be easily supplied is a real shocker.

Stem cell therapy cures most common cause of blindness in UK

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D

Doctors have taken a major step towards curing the most common form of blindness in the UK – age-related macular degeneration.

Douglas Waters, 86, could not see out of his right eye, but “I can now read the newspaper” with it, he says.

He was one of two patients given pioneering stem cell therapy at Moorfields Eye Hospital in London.

Cells from a human embryo were grown into a patch that was delicately inserted into the back of the eye.

Douglas, who is from London, developed severe age-related macular degeneration in his right eye three years ago.

[…]

The technique, published in Nature Biotechnology, starts with embryonic stem cells. These are a special type of cell that can become any other in the human body.

They are converted into the type of cell that makes up the retinal pigment epithelium and embedded into a scaffold to hold them in place.

The living patch is only one layer of cells thick – about 40 microns – and 6mm long and 4mm wide.

It is then placed underneath the rods and cones in the back of the eye. The operation takes up to two hours.

[…]

However, he does not call this a “cure” as completely normal vision is not restored.

[…]

So far the patients, the other is a woman in her early sixties, have maintained improved vision in the treated eye for a year.

They went from not being able to read with their affected eye at all, to reading 60 to 80 words per minute.

Eight more patients will take part in this clinical trial.

Doctors need to be sure it is safe. One concern is the transplanted cells could become cancerous, although there have been no such signs so far.

Source: Macular degeneration: ‘I’ve been given my sight back’ – BBC News

Orbitz Says Legacy Travel Site Likely Hacked, Affecting 880K

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Orbitz says one of its older websites may have been hacked, potentially exposing the personal information of people who made purchases online between Jan. 1, 2016 and Dec. 22, 2017.

The current Orbitz.com website was not involved in the incident. Orbitz is now owned by Expedia Inc. of Belleview, Washington.

Orbitz said Tuesday about 880,000 payment cards were impacted.

Data that was likely exposed includes name, address, payment card information, date of birth, phone number, email address and gender. Social Security information was not hacked, however. The company said evidence suggests that an attacker may have accessed information stored on the platform — which was for both consumers and business partners — between Oct. 1, 2017 and Dec. 22, 2017.

It said it discovered the data breach March 1.

Orbitz is offering those impacted a year of free credit monitoring and identity protection service in countries where available.

Source: Orbitz Says Legacy Travel Site Likely Hacked, Affecting 880K | Business News | US News

Oddly enough, it doesn’t say which site…

Telegram Loses Bid to Block Russia From Encryption Keys

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Telegram, the encrypted messaging app that’s prized by those seeking privacy, lost a bid before Russia’s Supreme Court to block security services from getting access to users’ data, giving President Vladimir Putin a victory in his effort to keep tabs on electronic communications.

Supreme Court Judge Alla Nazarova on Tuesday rejected Telegram’s appeal against the Federal Security Service, the successor to the KGB spy agency which last year asked the company to share its encryption keys. Telegram declined to comply and was hit with a fine of $14,000. Communications regulator Roskomnadzor said Telegram now has 15 days to provide the encryption keys.

Telegram, which is in the middle of an initial coin offering of as much as $2.55 billion, plans to appeal the ruling in a process that may last into the summer, according to the company’s lawyer, Ramil Akhmetgaliev. Any decision to block the service would require a separate court ruling, the lawyer said.

“Threats to block Telegram unless it gives up private data of its users won’t bear fruit. Telegram will stand for freedom and privacy,” Pavel Durov, the company’s founder, said on his Twitter page.

Putin signed laws in 2016 on fighting terrorism, which included a requirement for messaging services to provide the authorities with means to decrypt user correspondence. Telegram challenged an auxiliary order by the Federal Security Service, claiming that the procedure doesn’t involve a court order and breaches constitutional rights for privacy, according to documents.

The security agency, known as the FSB, argued in court that obtaining the encryption keys doesn’t violate users’ privacy because the keys by themselves aren’t considered information of restricted access. Collecting data on particular suspects using the encryption would still require a court order, the agency said.

“The FSB’s argument that encryption keys can’t be considered private information defended by the Constitution is cunning,” Akhmetgaliev, Telegram’s lawyer, told reporters after the hearing. “It’s like saying, ‘I’ve got a password from your email, but I don’t control your email, I just have the possibility to control.’”

Source: Telegram Loses Bid to Block Russia From Encryption Keys – Bloomberg

Windows 10 S (for Surface) and Cortana force you to use Edge and Bing, and Windows Mail forces links to open in Edge

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Windows 10 S, Microsoft’s new locked-down operating system that comes bundled with the Surface Laptop, won’t allow you to change the default Web browser away from Microsoft’s own Edge. Furthermore, Edge’s default search provider can’t be altered: Bing is all you get.

Curiously you can download other browsers from the Windows Store, such as Opera Mini, but Windows 10 S won’t let you set it as the default browser: if you try to open an HTML file, or click a link in another app, it will always open in Edge, according to Microsoft’s official FAQ on the topic.

The FAQ uses very direct language: “Microsoft Edge is the default web browser on Microsoft 10 S. The default search provider in Microsoft Edge and Internet Explorer cannot be changed.” It isn’t clear if OEMs will be able to override this feature of Windows 10 S.

It’s worth noting at this juncture that Windows 10 S, much like its spiritual predecessor Windows RT, will only run apps that you download from the Windows Store—and currently, neither Firefox or Chrome have been packaged up for the Windows Store. I can’t imagine that Google will be super-keen to bring Chrome to the Windows Store if Windows 10 S users can’t change the default browser.

Source: Windows 10 S forces you to use Edge and Bing | Ars Technica

Edge might be Windows 10’s built-in browser, but it definitely isn’t the most popular browser — NetMarketShare reported just under 4 percent usage share as of February 2018, slipping well below Chrome’s 59 percent. And now, it looks like the company may be trying to boost its share through software policies. The company is testing a Windows 10 preview release in the Skip Ahead ring which opens all Windows Mail web links in Edge, regardless of your app defaults. It provides the “best, most secure and consistent experience,” Microsoft argued.

The move isn’t coming completely out of the blue. Microsoft required Cortana users to rely on Bing search and open any web content in Edge, so this is arguably an extension of that policy.

Even so, the move is likely to irk at least some Windows 10 users. To start, its claims are highly subjective. Edge certainly isn’t immune to security exploits, and relying on it could actually create an inconsistent experience if you aren’t completely invested in Microsoft software. If you use Chrome on an Android phone, wouldn’t you want every link on your PC to open in Chrome so that they’re easier to retrieve when you’re on your handset? We can’t imagine that European antitrust regulators would be happy about Microsoft locking users into its own browser, either. We’ve asked Microsoft if it can comment on the concerns and will let you know if it has something to say.

Microsoft tests forcing Windows Mail users to open links in Edge

Booking Flights: Our Data Flies with Us – the huge dataset described

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Every time you book a flight, you generate personal data that is ripe for harvesting: information like the details on an ID card, your address, your passport information and your travel itinerary, as well as your frequent-flyer number, method of payment and travel preferences (dietary restrictions, mobility restrictions, etc.). All that data becomes part of a registry, in the form of a Passenger Name Record (PNR) – a generic name given to records created by aircraft operators or their authorised agents for each journey booked by or on behalf of any passenger.

When we book a flight or travel itinerary, the travel agent or booking website creates our PNR. Most airlines or travel agents choose to host their PNR databases on a specialised computer reservation system (CRS) or a Global Distribution System (GDS), which coordinates the information from all the travel agents and airlines worldwide, to avoid things like duplicated flight reservations. This means that CRSs/GDSs centralise and store vast amounts of data about travellers. Though we are focusing on air travel here, it is important to note that the PNR is not only flight-related. It can also include other services such as car rentals, hotel reservations and train trips.
[…]
A PNR isn’t necessarily created all at once. If we use the same agency or airline to book our flight and other services, like a hotel, the agency will use the same PNR. Therefore, information from many different sources will be gradually added to our PNR through different channels over time. That means the dataset is much larger than just the flight info: a PNR can contain data as important as our exact whereabouts at specific points in time.

What are the implications of all this for our privacy? The journalist and travel advocate Edward Hasbrouck has been researching and denouncing the PNR’s effects on privacy in the US for decades. In Europe, organisations like European Digital Rights (EDRi) have also criticised PNRs extensively through their advocacy and awareness campaigns. According to Hasbrouck:

PNR data reveals our associations, our activities, and our tastes and preferences. It shows where we went, when, with whom, for how long, and at whose expense. Through departmental and project billing codes, business travel PNR’s reveal confidential internal corporate and other organisation structures and lines of authority and show which people were involved in work together, even if they travelled separately. PNRs typically contain credit card numbers, telephone numbers, email addresses, and IP addresses, allowing them to be easily merged with financial and communications metadata

Your individual PNR also contains a section for free-text “remarks” that can be entered by the airline, the travel agency, a tour operator, a third-party call centre or the staff of the ground-handling contractor. Such texts might include sensitive and private information, like special meal requests and particular medical needs. This may seem innocuous, but information like special meal requests can indicate our religious or political affiliations, especially when it is cross-referenced with other details included in our PNR. Regardless of whether the profile assigned to us is accurate, the repercussions and implications of that profiling are concerning – especially in the absence of public awareness about them.
[…]
In the United States, PNRs are stored in the Automated Targeting System-Passenger (ATS-P), where they become part of an active database for up to five years (after the first six months, they are de-personalised and masked). After five years, the data is transferred to a dormant database for up to ten more years, where it remains available for counter-terrorism purposes for the full duration of its 15-year retention.

According to Edward Hasbrouck, PNRs cannot be deleted: once created, they are archived and retained in the Computer Reservation Data and You and/or Global Distribution Data and You (CRS/GDS), and can still be viewed, even if we never bought a ticket and cancelled our reservations:

“CRS’s retain flown, archived, purged, and deleted PNR’s indefinitely. It doesn’t really matter whether governments store copies of entire PNR’s or only portions of them, whether they filter out certain especially “sensitive” data from their copies of PNR’s, or for how long they retain them. As long as a government agency has the record locator or the airline name, flight number, and date, they can retrieve the complete PNR from the CRS. That’s especially true for the U.S. government, since even PNR’s created by airlines, travel agencies, tour operators, or airline offices in other countries, for flights within and between other countries that don’t touch the USA, are routinely stored in CRS’s based in the USA.
[…]
Under EU regulations, governments can retain PNR data for a maximum of five years, to allow law-enforcement officials to access it if necessary. The regulations state that after six months, the data is masked out or anonymised. But according to research by the EDRi, records are not necessarily anonymised or encrypted, and, in fact, the data can be easily re-personalised.
[…]
PNR is a relatively old system, pre-dating the internet as we know it today. Airlines have built their own systems on top of this, allowing passengers to make adjustments to their reservations using a six-character booking confirmation number or PNR locator. But although the PNR system was originally designed to facilitate the sharing of information rather than the protection of it, in the current digital environment and with the cyber-threats facing our data online, this system needs to be updated to keep up with the existing risks. PNRs are information-rich files are not only of interest for governments; they are also valuable to third parties – whether corporations or adversaries. Potential uses of the data could include anything from marketing research to hacks aimed at obtaining our personal information for financial scams or even doxxing or inflicting harm on activists.

According to Hasbrouck, the controls over who can access PNR data are insufficient, and there are no limitations on how CRS/GDS users (whether governments or travel agents) can access it. Furthermore, there are no records of when a CRS/GDS user has retrieved a PNR, from where they retrieved the record, or for what purpose. This means that any travel agent or any government can retrieve our PNR and access all the data it contains, no questions asked and without leaving a trace.
[…]
Photos of our tickets or luggage tags pose particular risks because of the sensitive information printed on them. In addition to our name and flight information, they also include our PNR locator, though sometimes only inside the barcode. Even if we cannot “see” information in the barcodes or sequences of letters and numbers on our tickets, other people may be able to derive meaning from them.

Source: Booking Flights: Our Data Flies with Us – Our Data Our Selves

Palantir has secretly been using New Orleans to test its predictive policing technology, was given huge access to lots of private data without oversight due to loophole

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The program began in 2012 as a partnership between New Orleans Police and Palantir Technologies, a data-mining firm founded with seed money from the CIA’s venture capital firm. According to interviews and documents obtained by The Verge, the initiative was essentially a predictive policing program, similar to the “heat list” in Chicago that purports to predict which people are likely drivers or victims of violence.

The partnership has been extended three times, with the third extension scheduled to expire on February 21st, 2018. The city of New Orleans and Palantir have not responded to questions about the program’s current status.

Predictive policing technology has proven highly controversial wherever it is implemented, but in New Orleans, the program escaped public notice, partly because Palantir established it as a philanthropic relationship with the city through Mayor Mitch Landrieu’s signature NOLA For Life program. Thanks to its philanthropic status, as well as New Orleans’ “strong mayor” model of government, the agreement never passed through a public procurement process.

In fact, key city council members and attorneys contacted by The Verge had no idea that the city had any sort of relationship with Palantir, nor were they aware that Palantir used its program in New Orleans to market its services to another law enforcement agency for a multimillion-dollar contract.

Even within the law enforcement community, there are concerns about the potential civil liberties implications of the sort of individualized prediction Palantir developed in New Orleans, and whether it’s appropriate for the American criminal justice system.

“They’re creating a target list, but we’re not going after Al Qaeda in Syria,” said a former law enforcement official who has observed Palantir’s work first-hand as well as the company’s sales pitches for predictive policing. The former official spoke on condition of anonymity to freely discuss their concerns with data mining and predictive policing. “Palantir is a great example of an absolutely ridiculous amount of money spent on a tech tool that may have some application,” the former official said. “However, it’s not the right tool for local and state law enforcement.”

Six years ago, one of the world’s most secretive and powerful tech firms developed a contentious intelligence product in a city that has served as a neoliberal laboratory for everything from charter schools to radical housing reform since Hurricane Katrina. Because the program was never public, important questions about its basic functioning, risk for bias, and overall propriety were never answered.
[…]
Palantir’s prediction model in New Orleans used an intelligence technique called social network analysis (or SNA) to draw connections between people, places, cars, weapons, addresses, social media posts, and other indicia in previously siloed databases. Think of the analysis as a practical version of a Mark Lombardi painting that highlights connections between people, places, and events. After entering a query term — like a partial license plate, nickname, address, phone number, or social media handle or post — NOPD’s analyst would review the information scraped by Palantir’s software and determine which individuals are at the greatest risk of either committing violence or becoming a victim, based on their connection to known victims or assailants.

The data on individuals came from information scraped from social media as well as NOPD criminal databases for ballistics, gangs, probation and parole information, jailhouse phone calls, calls for service, the central case management system (i.e., every case NOPD had on record), and the department’s repository of field interview cards. The latter database represents every documented encounter NOPD has with citizens, even those that don’t result in arrests. In 2010, The Times-Picayune revealed that Chief Serpas had mandated that the collection of field interview cards be used as a measure of officer and district performance, resulting in over 70,000 field interview cards filled out in 2011 and 2012. The practice resembled NYPD’s “stop and frisk” program and was instituted with the express purpose of gathering as much intelligence on New Orleanians as possible, regardless of whether or not they committed a crime.
[…]
NOPD then used the list of potential victims and perpetrators of violence generated by Palantir to target individuals for the city’s CeaseFire program. CeaseFire is a form of the decades-old carrot-and-stick strategy developed by David Kennedy, a professor at John Jay College in New York. In the program, law enforcement informs potential offenders with criminal records that they know of their past actions and will prosecute them to the fullest extent if they re-offend. If the subjects choose to cooperate, they are “called in” to a required meeting as part of their conditions of probation and parole and are offered job training, education, potential job placement, and health services. In New Orleans, the CeaseFire program is run under the broader umbrella of NOLA For Life, which is Mayor Landrieu’s pet project that he has funded through millions of dollars from private donors.

According to Serpas, the person who initially ran New Orleans’ social network analysis from 2013 through 2015 was Jeff Asher, a former intelligence agent who joined NOPD from the CIA. If someone had been shot, Serpas explained, Asher would use Palantir’s software to find people associated with them through field interviews or social media data. “This data analysis brings up names and connections between people on FIs [field interview cards], on traffic stops, on victims of reports, reporting victims of crimes together, whatever the case may be. That kind of information is valuable for anybody who’s doing an investigation,” Serpas said.
[…]
Of the 308 people who participated in call-ins from October 2012 through March 2017, seven completed vocational training, nine completed “paid work experience,” none finished a high school diploma or GED course, and 32 were employed at one time or another through referrals. Fifty participants were detained following their call-in, and two have since died.

By contrast, law enforcement vigorously pursued its end of the program. From November 2012, when the new Multi-Agency Gang Unit was founded, through March 2014, racketeering indictments escalated: 83 alleged gang members in eight gangs were indicted in the 16-month period, according to an internal Palantir presentation.
[…]
Call-ins declined precipitously after the first few years. According to city records, eight group call-ins took place from 2012 to 2014, but only three took place in the following three years. Robert Goodman, a New Orleans native who became a community activist after completing a prison sentence for murder, worked as a “responder” for the city’s CeaseFire program until August 2016, discouraging people from engaging in retaliatory violence. Over time, Goodman noticed more of an emphasis on the “stick” component of the program and more control over the non-punitive aspects of the program by city hall that he believes undermined the intervention work. “It’s supposed to be ran by people like us instead of the city trying to dictate to us how this thing should look,” he said. “As long as they’re not putting resources into the hoods, nothing will change. You’re just putting on Band-Aids.”

After the first two years of Palantir’s involvement with NOPD, the city saw a marked drop in murders and gun violence, but it was short-lived. Even former NOPD Chief Serpas believes that the preventative effect of calling in dozens of at-risk individuals — and indicting dozens of them — began to diminish.

“When we ended up with nearly nine or 10 indictments with close to 100 defendants for federal or state RICO violations of killing people in the community, I think we got a lot of people’s attention in that criminal environment,” Serpas said, referring to the racketeering indictments. “But over time, it must’ve wore off because before I left in August of ‘14, we could see that things were starting to slide”

Nick Corsaro, the University of Cincinnati professor who helped build NOPD’s gang database, also worked on an evaluation of New Orleans’ CeaseFire strategy. He found that New Orleans’ overall decline in homicides coincided with the city’s implementation of CeaseFire program, but the Central City neighborhoods targeted by the program “did not have statistically significant declines that corresponded with November 2012 onset date.”
[…]
The secrecy surrounding the NOPD program also raises questions about whether defendants have been given evidence they have a right to view. Sarah St. Vincent, a researcher at Human Rights Watch, recently published an 18-month investigation into parallel construction, or the practice of law enforcement concealing evidence gathered from surveillance activity. In an interview, St. Vincent said that law enforcement withholding intelligence gathering or analysis like New Orleans’ predictive policing work effectively kneecaps the checks and balances of the criminal justice system. At the Cato Institute’s 2017 Surveillance Conference in December, St. Vincent raised concerns about why information garnered from predictive policing systems was not appearing in criminal indictments or complaints.

“It’s the role of the judge to evaluate whether what the government did in this case was legal,” St. Vincent said of the New Orleans program. “I do think defense attorneys would be right to be concerned about the use of programs that might be inaccurate, discriminatory, or drawing from unconstitutional data.”

If Palantir’s partnership with New Orleans had been public, the issues of legality, transparency, and propriety could have been hashed out in a public forum during an informed discussion with legislators, law enforcement, the company, and the public. For six years, that never happened.

Source: Palantir has secretly been using New Orleans to test its predictive policing technology – The Verge

One of the big problems here is that there is no knowledge and hardly any oversight on the program. There is no knowledge if the system is being implemented fairly or cost effectively (costs are huge!) or even if it works. It seemed to have worked for a while but the effects seemed also to drop off after two years in operations, mainly because they used the “stick” method to counter crime but more and more got rid of the “carrot”. The amount of private data given to Palantir without any discussion or consent is worrying to say the least.

The Lottery Hackers

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That’s when it hit him. Right there, in the numbers on the page, he noticed a flaw—a strange and surprising pattern, like the cereal-box code, written into the fundamental machinery of the game. A loophole that would eventually make Jerry and Marge millionaires, spark an investigation by a Boston Globe Spotlight reporter, unleash a statewide political scandal and expose more than a few hypocrisies at the heart of America’s favorite form of legalized gambling.
[…]
This particular game was called Winfall. A ticket cost $1. You picked six numbers, 1 through 49, and the Michigan Lottery drew six numbers. Six correct guesses won you the jackpot, guaranteed to be at least $2 million and often higher. If you guessed five, four, three, or two of the six numbers, you won lesser amounts. What intrigued Jerry was the game’s unusual gimmick, known as a roll-down: If nobody won the jackpot for a while, and the jackpot climbed above $5 million, there was a roll-down, which meant that on the next drawing, as long as there was no six-number winner, the jackpot cash flowed to the lesser tiers of winners, like water spilling over from the highest basin in a fountain to lower basins. There were lottery games in other states that offered roll-downs, but none structured quite like Winfall’s. A roll-down happened every six weeks or so, and it was a big deal, announced by the Michigan Lottery ahead of time as a marketing hook, a way to bring bettors into the game, and sure enough, players increased their bets on roll-down weeks, hoping to snag a piece of the jackpot.

The brochure listed the odds of various correct guesses. Jerry saw that you had a 1-in-54 chance to pick three out of the six numbers in a drawing, winning $5, and a 1-in-1,500 chance to pick four numbers, winning $100. What he now realized, doing some mental arithmetic, was that a player who waited until the roll-down stood to win more than he lost, on average, as long as no player that week picked all six numbers. With the jackpot spilling over, each winning three-number combination would put $50 in the player’s pocket instead of $5, and the four-number winners would pay out $1,000 in prize money instead of $100, and all of a sudden, the odds were in your favor. If no one won the jackpot, Jerry realized, a $1 lottery ticket was worth more than $1 on a roll-down week—statistically speaking.

“I just multiplied it out,” Jerry recalled, “and then I said, ‘Hell, you got a positive return here.’”
[…]
This was an uncomfortable leap for a guy with no experience in gambling, but if he stopped now, he would never know if his theory was correct. During the next roll-down week, he returned to Mesick and made a larger bet, purchasing $3,400 in Winfall tickets. Sorting 3,400 tickets by hand took hours and strained his eyes, but Jerry counted them all right there at the convenience store so that Marge would not discover him. This time he won $6,300—an impressive 46 percent profit margin. Emboldened, he bet even more on the next roll-down, $8,000, and won $15,700, a 49 percent margin.
[…]
he lottery is like a bank vault with walls made of math instead of steel; cracking it is a heist for squares. And yet a surprising number of Americans have pulled it off. A 2017 investigation by the Columbia Journalism Review found widespread anomalies in lottery results, difficult to explain by luck alone. According to CJR’s analysis, nearly 1,700 Americans have claimed winning tickets of $600 or more at least 50 times in the last seven years, including the country’s most frequent winner, a 79-year-old man from Massachusetts named Clarance W. Jones, who has redeemed more than 10,000 tickets for prizes exceeding $18 million.
[…]
he and Marge were willing to do the grunt work, which, as it turned out, was no small challenge. Lottery terminals in convenience stores could print only 10 slips of paper at a time, with up to 10 lines of numbers on each slip (at $1 per line), which meant that if you wanted to bet $100,000 on Winfall, you had to stand at a machine for hours upon hours, waiting for the machine to print 10,000 tickets. Code in the purchase. Push the “Print” button. Wait at least a full minute for the 10 slips to emerge. Code in the next purchase. Hit “Print.” Wait again. Jerry and Marge knew all the convenience store owners in town, so no one gave them a hard time when they showed up in the morning to print tickets literally all day. If customers wondered why the unassuming couple had suddenly developed an obsession with gambling, they didn’t ask. Sometimes the tickets jammed, or the cartridges ran out of ink. “You just have to set there,” Jerry said.

The Selbees stacked their tickets in piles of $5,000, rubber-banded them into bundles and then, after a drawing, convened in their living room in front of the TV, sorting through tens or even hundreds of thousands of tickets, separating them into piles according to their value (zero correct numbers, two, three, four, five). Once they counted all the tickets, they counted them again, just to make sure they hadn’t missed anything. If Jerry had the remote, they’d watch golf or the History Channel, and if Marge had it, “House Hunters” on HGTV. “It looked extremely tedious and boring, but they didn’t view it that way,” recalled their daughter Dawn. “They trained their minds. Literally, they’d pick one up, look at it, put it down. Pick one up, put it down.” Dawn tried to help but couldn’t keep pace; for each ticket she completed, Jerry or Marge did 10.
[…]
That June, Jerry created a corporation to manage the group. He gave it an intentionally boring name, GS Investment Strategies LLC, and started selling shares, at $500 apiece, first to the kids and then to friends and colleagues in Evart. Jerry would eventually expand the roster to 25 members, including a state trooper, a parole officer, a bank vice president, three lawyers and even his personal accountant, a longtime local with a smoker’s scratchy voice named Steve Wood. Jerry would visit Wood’s storefront office downtown, twist the “Open” sign to “Closed,” and seek his advice on how to manage the group.
[…]
And business was good. By the spring of 2005, GS Investment Strategies LLC had played Winfall on 12 different roll-down weeks, the size of the bets increasing along with the winnings. First $40,000 in profits. Then $80,000. Then $160,000. Marge squirreled her share away in a savings account. Jerry bought a new truck, a Ford F350, and a camping trailer that hooked onto the back of it. He also started buying coins from the U.S. Mint as a hedge against inflation, hoping to protect his family from any future catastrophe. He eventually filled five safe deposit boxes with coins of silver and gold.
[…]
A mathematics major in his final semester, Harvey had been researching lottery games for an independent study project, comparing the popular multistate games Powerball and MegaMillions to see which offered players a better shot at winning. He’d also analyzed different state games, including Cash WinFall, and it hadn’t taken him long to spot its flaw: On a roll-down week, a $2 lottery ticket was worth more than $2, mathematically.

Within days, Harvey had recruited some 50 people to pony up $20 each, for a total of $1,000, enough to buy 500 Cash WinFall tickets for the February 7 roll-down drawing. The Patriots won the Super Bowl on February 6, and the following day, the MIT group took home $3,000, for a $2,000 profit.

Curiously enough, the MIT students weren’t the only ones playing Cash WinFall for high stakes that day. A biomedical researcher at Boston University, Ying Zhang, had also discovered the flaw, after an argument with friends about the nature of the lottery. Believing it to be exploitative, Zhang had researched the Massachusetts State Lottery to bolster his point. Then he found the glitch in Cash WinFall, and as happens so often in America, a skeptic of capitalism became a capitalist. Zhang encouraged friends to play and formed his own betting club, Doctor Zhang Lottery Club Limited Partnership. His group began wagering between $300,000 and $500,000 on individual roll-down weeks, and eventually Zhang quit his job as a biomedical researcher to focus on the lottery full time. He bought tickets in bulk at a convenience store near his home, in the Boston suburb of Quincy, and stored the losing tickets in boxes in his attic until the weight made his ceiling crack.

As energetically as Zhang played the game, however, he couldn’t match the budding lottery moguls at MIT. After the first roll-down, Harvey assembled 40 to 50 regular players—some of them professors with substantial resources—and recruited his classmate, Yuran Lu, to help manage the group. Lu was an electrical engineering, computer science and math major with a mischievous streak: one time, to make a point about security, he’d stolen 620 passwords from students and professors. Now he helped Harvey form a corporation, named Random Strategies LLC, after their dorm. Their standard wager on a roll-down week was $600,000—300,000 tickets. Unlike the Selbees, who allowed the computer to pick numbers for them (“Quic Pics”), the MIT students preferred to choose their own, which avoided duplicates but also meant that the students had to spend weeks filling in hundreds of thousands of tiny ovals on paper betting slips.

Source: The Lottery Hackers – The Huffington Post

A great article on how three groups of people were hacking this lottery and how it all ended.

MIT builds Neural network chip with 95% reduction in power consumption, allowing it to be used in a mobile

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Most recent advances in artificial-intelligence systems such as speech- or face-recognition programs have come courtesy of neural networks, densely interconnected meshes of simple information processors that learn to perform tasks by analyzing huge sets of training data.

But neural nets are large, and their computations are energy intensive, so they’re not very practical for handheld devices. Most smartphone apps that rely on neural nets simply upload data to internet servers, which process it and send the results back to the phone.

Now, MIT researchers have developed a special-purpose chip that increases the speed of neural-network computations by three to seven times over its predecessors, while reducing power consumption 94 to 95 percent. That could make it practical to run neural networks locally on smartphones or even to embed them in household appliances.

“The general processor model is that there is a memory in some part of the chip, and there is a processor in another part of the chip, and you move the data back and forth between them when you do these computations,” says Avishek Biswas, an MIT graduate student in electrical engineering and computer science, who led the new chip’s development.

“Since these machine-learning algorithms need so many computations, this transferring back and forth of data is the dominant portion of the energy consumption. But the computation these algorithms do can be simplified to one specific operation, called the dot product. Our approach was, can we implement this dot-product functionality inside the memory so that you don’t need to transfer this data back and forth?”

Source: Neural networks everywhere | MIT News

Hey Microsoft, Stop Installing Apps On My PC Without Asking

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I’m getting sick of Windows 10’s auto-installing apps. Apps like Facebook are now showing up out of nowhere, and even displaying notifications begging for me to use them. I didn’t install the Facebook app, I didn’t give it permission to show notifications, and I’ve never even used it. So why is it bugging me?

Windows 10 has always been a little annoying about these apps, but it wasn’t always this bad. Microsoft went from “we pinned a few tiles, but the apps aren’t installed until you click them” to “the apps are now automatically installed on your PC” to “the automatically installed apps are now sending you notifications”. It’s ridiculous.
The “Microsoft Consumer Experience” Is Consumer-Hostile…

This is all thanks to the “Microsoft Consumer Experience” program, which can’t be disabled on normal Windows 10 Home or Professional systems. That’s why every Windows 10 computer you start using has these bonus apps. The exact apps preinstalled can vary, but I’ve never seen a Windows 10 PC without Candy Crush.

The Microsoft Consumer Experience is actually a background task that runs whenever you sign into a Windows 10 PC with a new user account for the first time. It kicks into gear and automatically downloads apps like Candy Crush Soda Saga, FarmVille 2: Country Escape, Facebook, TripAdvisor, and whatever else Microsoft feels like promoting.

You can uninstall the apps from your Start menu, and they shouldn’t come back on your user account the same hardware. However, the apps will also come back whenever you sign into a new PC with the same Microsoft account, forcing you to remove them on each device you use. And, if someone signs into your same PC with their own Microsoft account, Microsoft will “helpfully” download those apps for their account as well. There’s no way to tell Microsoft “stop downloading these apps on my PC” or “I never want these apps on this Microsoft account”.
…and Microsoft Won’t Let Us Disable It

There is, technically, a way to disable this and stop Windows from installing these apps…but it’s only for Windows 10 Enterprise and Education users. Even if you spent $200 for a Windows 10 Professional license because you want to use your PC for business, Microsoft won’t let you stop the “Consumer Experience” on a professional PC.

Source: Hey Microsoft, Stop Installing Apps On My PC Without Asking

Together with Windows 10 sending private data to Redmond without permission this is another reason I have left the world of MS operating systems. I now use Linux Mint.

119,000 Passports and Photo IDs of FedEx Customers Found on Unsecured Amazon Server

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Thousands of FedEx customers were exposed after the company left scanned passports, drivers licenses, and other documentation on a publicly accessible Amazon S3 server.

The scanned IDs originated from countries all over the world, including the United States, Mexico, Canada, Australia, Saudi Arabia, Japan, China, and several European countries. The IDs were attached to forms that included several pieces of personal information, including names, home addresses, phone numbers, and zip codes.

The server, discovered by researchers at the Kromtech Security Center, was secured as of Tuesday.

According to Kromtech, the server belonged to Bongo International LLC, a company that aided customers in performing shipping calculations and currency conversations, among other services. Bongo was purchased by FedEx in 2014 and renamed FedEx Cross-Border International a little over a year later. The service was discontinued in April 2017.

Source: 119,000 Passports and Photo IDs of FedEx Customers Found on Unsecured Amazon Server

Tesla’s Amazon Cloud Account Hacked to Mine Cryptocurrency

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An unidentified hacker or hackers broke into a Tesla-owned Amazon cloud account and used it to “mine” cryptocurrency, security researchers said. The breach also exposed proprietary data for the electric carmaker.

The researchers, who worked for RedLock, a 3-year-old cybersecurity startup, said they discovered the intrusion last month while trying to determine which organization left credentials for an Amazon Web Services (AWS) account open to the public Internet. The owner of the account turned out to be Tesla, they said.

“We weren’t the first to get to it,” Varun Badhwar, CEO and cofounder of RedLock, told Fortune on a call. “Clearly, someone else had launched instances that were already mining cryptocurrency in this particular Tesla environment.”

The incident is the latest in a string of so-called cryptojacking attacks, which involve thieves hijacking unsuspecting victims’ computers to generate virtual currencies like Bitcoin. The schemes have seen a resurgence in popularity as cryptocurrency prices have soared over the past year.

Earlier this month, websites for the U.S. federal court system and the U.K.’s National Health Service roped their visitors into similar virtual money-minting operations.

Source: Tesla’s Amazon Cloud Account Hacked to Mine Cryptocurrency | Fortune

Uzi Nissan Spent 8 Years Fighting The Car Company With His Name. He Nearly Lost Everything To Win. The legal system doesn’t work very well if you have no money.

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Nissan the car company never really cared who Uzi Nissan was. Then it decided he had something it wanted very much—the website www.nissan.com, which he created for his small retail computer business in 1994—and it sued him for $10 million. When the two Nissans went to war, Uzi Nissan prevailed in the end, but lost almost everything along the way.

If you visit nissan.com expecting a polished presentation of Nissan’s latest lineup, you’re in for quite a shock. What you land in is Uzi Nissan’s corner of the internet; a shrine to the years of his life spent fighting what is now the largest car company on the planet.

You’re greeted with a straight-out-of-the-’90s web design with 3D-effect link buttons, minimal advertising, crossed-out Nissan Motor badges and a Nissan Computer logo design that seems to resemble a stamped business card.
[…]
If you further postpone your quest to get a quote on an Altima or a Rogue Sport and spend time to explore the site, you find pages and pages of articles on the Nissan Motor vs. Nissan Computer lawsuit, taught in business schools and law schools as one of the most notable domain cases from the age of the dotcom bubble.

“The study there is that you should first have your domain before you decide your name of business, and in law school it’s just to show that sometimes even the little guy can win,” he said.
[…]
At the time, it didn’t seem like the start of an all-consuming legal battle, a David vs. Goliath fight that took nearly 10 years and cost the small business owner millions of dollars—to say nothing of the incalculable toll on his personal life.

Source: Uzi Nissan Spent 8 Years Fighting The Car Company With His Name. He Nearly Lost Everything To Win

The story is well told and shows you how ridiculous it is that this guy who clearly had prior ownership to the Nissan name and domain name had to pony up near to $3m and 8 years of his life to keep what is rightfully his. There is no punishment for the big guy throwing resources to wast another person’s time and money in the courts.