Category Archives: Technology

Travelling With Technology – Some Tips From Master

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Tips for taking great city photos with your smartphone

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The Virus Top Ten Digital Distruction

The Virus Top Ten Digital Distruction

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Here are the top ten most destructive viruses unleashed over the last decade into the digital domain.

1. Storm Worm

Storm Worm was released in 2007 anc was rumoured to have hailed from Russia. It came in the form of an email link, usually with an important headline to grab the victim’s attention. When the victim clicks the link the code is inserted and payload with a backdoor into the system is opened. It infected over 10 million computers worldwide.

2. Conficker

Conficker was a 2008 worm that infected an estimated 15 million Windows computers worldwide. The French Navy, UK Ministry of Defence, hospitals and local police forces were affected. It was spread via Facebook, Skype and mail services, and infected networked computers with a key logger that the hacker could use to record your keyboard strokes

3. Daprosy Worm

2009 saw the release of ihe Daprosy Worm whereby an estimated 20 million computers were infected with a key logger. What made this such a dangerous virus was that it remained active in Windows safe Mod  ? so it was very difficult to r emove.

4. Stuxnet

Stuxnet was rumoured to have been a US Intelligence created virus that was designed to Infect Iranian nuclear power plants, thus stopping them from potentially creating weapons grade material Whether you believe that or not, it was one  the worst viruses to appear in moden times.

5. Duqu

Duqu was released in 2011 and shared many characteristics with Stuxnct. However Duqu had different roles: it would work as a key logger, to steal digital certificates, gather information about an infected PC, or completely wipe the contents of any connected hard drives. Interestingly, parts of the Duqu code were written in an unknown high level programming language.

6. Shamoon

Shamoon was discovered in 2012 and developed to infect the Windows kernel, the core code of [he operating system. It successfully managed to wipe the contents of millions of hard drives and was rumoured to be used in cyber espionage in the energy industry,

7. CryptoLocker

CryptoLocker is a ransomware infection that first appeared in 2015, As with most ransomware code it locks and encrypts your entire hard drive and offers to unlock them if the victim pays up to $300. Remarkably, the code
was able to delete itself whilst still keeping the files encrypted and locked.

8. CryptoLocker

2014 Regin virus was spread via fake websites and infected tens of millions of computers. Rumour has it that it was a joint US and UK Intelligence created virus for global digital surveillance but well leave chat for the conspiracy theorists to argue over. Nevertheless, it managed to send information of the victims computer back to an unknown location.

9. Rombertik’s Endless Loop

Rombertik’s Endless Loop is an interesting, if somewhat deadly, virus to have sprung up in 2015. When infected, the virus wiII alter and delete key boot files for Windows computers then force them to reboot. With the boot files, missing or altered the Windows PC will cant nuatly boot and reboot itself until you re- nstall the OS.

10. Tiny Banker

Tiny Banker is an information and packet sniffer virus that will record and onIine banking detaiIs the victim enters in their computer. That information is then sort back to several servers which the hackers can then use to access your bank accounts. It’s estimated that hundreds of millions were stolen in 2016 thanks toTiny Banker.

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The Politics of YouTube’s AI

The Politics of YouTube’s AI

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If somebody uploads a video of extreme violence and gore — say, of individuals foaming at the mouth from poisoning, or a father cradling their dying infant — should YouTube’s AI flag and remove it from their site? The obvious answer is: yes.

Or maybe not.

The Scale of YouTube Censorship

Around 300 hours of video is uploaded to YouTube every minute, of every day. The unimaginable scale of content that makes it on the site means that humans alone cannot properly censor all of the violent, explicit or otherwise objectionable material that might be submitted for publication.

Luckily, Google (YouTube’s parent company) has developed algorithms that use advanced machine learning techniques to snuff out harmful content before any damage is done. In just the first quarter of 2019, for example, just over eight million videos were blocked from the site. Of those eight million, over six million were identified and removed by YouTube’s AI, 70 percent of them before a single view was recorded. When it comes to violent extremist content, the numbers fair even better. Even as early as 2017, YouTube’s AI was able to catch 98 percent of terrorist videos uploaded to the site.

Those kinds of numbers constitute a resounding success, considering that image recognition technology today is still a growing, not fully-developed field, and considering the sheer breadth of material these algorithms have to push through. But the rate at which YouTube’s AI removes bad material tells you only part of the story. For all the dangerous videos taken offline, there are also plenty of false positives.

Sensitivity

Say you’re a mall cop, and a few thousand people walk through the doors of your mall every day. How closely will you screen those people who come in and out? How many will you stop, and vet for security purposes? Probably not many, because of the nature of what’s being protected.

But what if you’re a TSA agent?

The nature of what’s being protected obliges you to be more careful in your screening. TSA agents constantly screen airline passengers for even the slightest suspicions, because the risk of allowing a threat to pass is too great.

We might call the difference between being a mall cop and being a TSA agent a sensitivity.

It turns out that sensitivity is just as much a consideration for security-oriented software as it is security-oriented professionals. In the cybersecurity space, for example, malware is often masked to look like ordinary data, in order to try and pass through to a vulnerable computer undetected. Security programs, therefore, must be sensitive to anything that even looks like a virus. Perhaps, for a personal computer, the filter can let a little more pass by. But what about a highly sensitive government computer network? In this case, a program must be tuned to be highly sensitive — to perk its ears up at any warning, even if it means producing many false positives along the way.

Ulrich Kaiser is a music theory teacher from Germany. Last year, after one of his educational videos was taken offline by YouTube’s Content ID system, which logs copyright works and checks that they’re not copied and misused elsewhere on the platform. He wondered why perfectly legal music was being banned from the site, so he began an experiment. He opened a new YouTube account, and began diligently posting public domain music written by long-dead composers. Almost inevitably, each time, his videos were flagged as copyright infringements, and blocked from the site.

Why were the videos being taken down so predictably? For the same reason TSA agents over-screen airline passengers. Meredith Rose, a copyright expert for Public Knowledge, told Vice’s Motherboard: “Algorithmic matching is always going to be imprecise, and companies are legally incentivized to be over-inclusive in their filtering.” Because algorithms aren’t perfect, and international laws are varied and complicated, YouTube is incentivized to over-censor the content on their site, and accept that a certain number of false positives will be created in the process. Music teachers may be rightly dissatisfied, but the alternative — under-censoring — would be far worse.

Consequences of Doing the Right Thing

The amount of content that must be processed every day, coupled with the consequences of publishing dangerous material, means that YouTube’s overseers have, understandably, turned the knob on their censorship algorithms to high.

Unfortunately, it’s not just old classical music that’s taken down by the AI. In February of this year, multiple channels related to Pokemon Go and Club Penguin were flagged for displaying prohibited sexual content. It turns out that YouTube’s AI picked up on their use of the abbreviation “CP”, which it interpreted as reference to child pornography (in Pokemon Go, CP refers to “Combat Power”, and in Club Penguin, CP simply refers to the title of the game). Just a few weeks back, the same AI began flagging videos of fighting robots (a niche sport), interpreting the videos as demonstrations of animal cruelty.

Whenever these false positives arise, they cause a bit of a stir, they’re dealt with, and Google’s AI becomes better for it. A brief interruption in robot fighting is a small price to pay for keeping violent and extreme material off of the platform.

But it’s not always so simple as that. Sometimes, the violent and extreme overlaps with the legitimate and important. I asked you at the beginning of this article: should YouTube’s AI ban video of people — infants, even — being poisoned and dying? The answer seemed, obviously, to be yes.

When journalists and human rights activists on the ground during Syria’s civil war attempted to document the atrocities that Bashar al-Assad’s government was enacting on its people, they turned to YouTube for help. They started taking videos of the atrocities taking place, to show the world just how bad things were. The videos showed horrific violence: people being poisoned, people dying, even children and infants dying. And then, over one hundred thousand of those videos were taken down by YouTube censorship algorithms.

YouTube is an immense platform, with huge power to affect positive change in the world, and a huge responsibility to keep ordinary people safe from harm. The AI that underpins it all is remarkable — almost unbelievably effective — and also imperfect, with a penchant for gaffes both comical and harmful. The good thing is: it’s getting better every year.

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Twitter Embed Example

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Post with Vimeo Video Example

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