Never Let Down Your Computer Virus Awareness

Operating in today’s internet shrouded atmosphere is getting to be like playing in one of those first person shooter video games where the most aware succeed and the oblivious become chowder. Everyone is at risk from the high profile business to the private user. Even government and industrial networks of various countries have taken big hits from an array of dangerous computer viruses to hit the internet since its inception.

So, indeed, you are in a sort of wild-west arena when you logon, an aptitude for recognizing threats has had to become a staple any business, government or private user can’t be without. Having a top of the line anti-virus software will go a long way towards creating your force field. However, you still have to possess the skill to maneuver around the computer bombs that are there if you “click it” and some, these days, don’t even require a “click”.

Protecting today’s on-line atmosphere is no short of big business. The hackers will keep on trying and the anti-virus companies will keep developing the revisions of their software to combat them. This threat, and its apparent, will always be out there. Hackers are getting more sophisticated and complex as the clock ticks as well. While it is unclear whether the powers that be thought in depth of the attacks that could happen, the launch of the internet was definitely the future. The earliest hacks and implementation of viruses no doubt, had to originate from an individual with an idea to cause havoc. This practice caught like wildfire and created some of the worst viruses in the short history of the internet.

From the early 1990’s on, dangerous and damaging viruses have shocked the world. Take the virus “NIMDA” for instance. In 2001, a week after the 9/11 attack, this virus affected millions of computers. NIMDA’s main thrust was to slow down Internet traffic resulting in widespread network shutdowns. Another, in 2006 was a malicious Trojan horse program called “Storm Worm”. Storm Worm   suckered users into clicking on a subject line in their email; “230 die as storm batters Europe”. Of course the subject line was a fraud and users clicked on the fake link which would enable the perpetrator offsite    to operate a PC remotely. They utilized this path to send spam throughout the Internet. It was estimated Storm Worm affected 10 million PCs.

In 1998, one of the most destructive of viruses came to play. The “CIH” or “Chernobyl virus” infected the Windows 95 and 98 executable file and remained in the machines memory. It would constantly infect other executables within the machine. It is estimated that the CIH virus caused 250 million worth of destruction. 1999 brought in a macro-virus called “Melissa” it was a mass mailer virus that activated in the machine when the user clicked on an email link. The email came from a known source so it would appear ok, especially when the title was ” here is the document you asked for don’t show anyone else “The virus would then immediately seek out the first 50 users listed in the the users Outlook address book and email itself to them. This virus was one of the first utilized in email attachment, “Melissa “caused an estimated $300-$600 million in damage.

And it went on, in 2003, the “SQL Slammer” or “Sapphire” virus targeted servers by generating random IP addresses and discharging itself  this worm affected many businesses, banks and community operations including significant services provided by Bank of America; Continental Airlines and Seattle’s 911 emergency system to name a few. Estimated losses were between 950 million and 1 .2 billion.

Others such as the “Code Red” virus in 2001 activated on July 13 of that year. This virus did not require you to open an email attachment. It simply needed an open Internet connection and then gave you an opening webpage that said “Hacked by Chinese”; it brought down an estimated 400,000 servers including the White House Web server. Its damaging effect is estimated $2.6 billion loss.  The “SobigF” virus got in machines by an email telling the user that they have a security issue, when opened the intruder sends itself and traps the entire address book. This virus replicated itself to the tune of infecting millions of PC’s world-wide. Damages were estimated in the 3-4 billion range.

The first on to do the most damage was the “My Doom” or “Novarg” virus. On 26 January 2000 this virus circled the globe via email swiftly and 152 million computers and countless servers went on the blip. Creation of a huge “denial of service attack” and crippled computer atmospheres causing damages worldwide estimated at 30 billion.

Recent dangerous viruses have been “Poison Ivy” a remote access Trojan were the perpetrator uses backdoor technology to infect the user’s computer .Once installed the perpetrator has control of everything including record audio and video. This virus targets personal information to compromise identities that were proven to be bought and sold globally. This included online banking, shopping, and social security number and birth information reaping.

Cornficker, in 200i is a worm that targeted stealing financial data. A   very complex, difficult to stop virus, Cornficker caused the creation of a coalition of experts decided to stop it.  It was also called “Superbug”. The fact that this virus got into where it wanted and was able to do just about everything stumped. Cornficker has reconfigured several times and each time its effects are more sophisticated. Incredibly, the perpetrators have designed it to track the efforts taken to eradicate it. .

We have a very unique responsibility, being “on-line”. The internet is, at this point, just like any town on the map. There are places to go; there are places not to go. There are places in the internet that you might have to go to that are laced with lurking hackers just waiting for users to make that fateful
“click”. A good part of the battle can be waged here by just being vigilant. While you’re doing your financials, the stock market, shopping and all the day-to-day things that technology has provided you with that “one touch” to get to.

While aptitude to recognizing the “baddies” out there is a strong first suite, you’ll need help. The root of your defense lies in making sure you have a good Anti-Virus program, making sure it is always running and also your virus database is updated very often. Most of the anti-virus software out there has options for making all these concerns automatic. If you do, make sure you check they are all running as scheduled periodically. There are viruses that serve as precursors to bigger threats. What they do is literally turn-off all your anti-virus mechanisms without you knowing it until it’s too late.

So, be careful out there in your computing. Learn the signs that there is something amiss and act on it before taking another click. Once you get to know the common “this doesn’t look right” occurrence, the harder ones to recognize will be more understandable. One tip here, personnel users (because most businesses will not let users do this) DO NOT download any .EXE (executable) program or file without running it through the scanner. You might just be saving your computers life.


Brian J. Schweikert “Never Let Down Your Computer Virus Awareness”

Sabre88 LLC. N.p., Web. 19 October. 2016.

Editor’s note: Original Sources;


Secret Behind Artificial Intelligence’s Preposterous Power

Spookily powerful artificial intelligence (AI) systems may work so well because their structure exploits the fundamental laws of the universe, new research suggests.

The new findings may help answer a longstanding mystery about a class of artificial intelligence that employ a strategy called deep learning. These deep learning or deep neural network programs, as they’re called, are algorithms that have many layers in which lower-level calculations feed into higher ones. Deep neural networks often perform astonishingly well at solving problems as complex as beating the world’s best player of the strategy board game Go or classifying cat photos, yet know one fully understood why.

It turns out, one reason may be that they are tapping into the very special properties of the physical world, said Max Tegmark, a physicist at the Massachusetts Institute of Technology (MIT) and a co-author of the new research.

The laws of physics only present this “very special class of problems” — the problems that AI shines at solving. “This tiny fraction of the problems that physics makes us care about and the tiny fraction of problems that neural networks can solve are more or less the same.

Last year, AI accomplished a task many people thought impossible: DeepMind, Google’s deep learning AI system, defeated the world’s best Go player after trouncing the European Go champion. The feat stunned the world because the number of potential Go moves exceeds the number of atoms in the universe, and past Go-playing robots performed only as well as a mediocre human player.

But even more astonishing than DeepMind’s utter rout of its opponents was how it accomplished the task.

“The big mystery behind neural networks is why they work so well,” said study co-author Henry Lin, a physicist at Harvard University. “Almost every problem we throw at them, they crack.”

For instance, DeepMind was not explicitly taught Go strategy and was not trained to recognize classic sequences of moves. Instead, it simply “watched” millions of games, and then played many, many more against itself and other players.

Like newborn babies, these deep-learning algorithms start out “clueless,” yet typically outperform other AI algorithms that are given some of the rules of the game in advance.

Another long-held mystery is why these deep networks are so much better than so-called shallow ones, which contain as little as one layer. Deep networks have a hierarchy and look a bit like connections between neurons in the brain, with lower-level data from many neurons feeding into another “higher” group of neurons, repeated over many layers. In a similar way, deep layers of these neural networks make some calculations, and then feed those results to a higher layer of the program, and so on, he said.

To understand why this process works, Tegmark and Lin decided to flip the question on its head.

“Suppose somebody gave you a key. Every lock you try, it seems to open. One might assume that the key has some magic properties. But another possibility is that all the locks are magical. In the case of neural nets, I suspect it’s a bit of both,” Lin said.

One possibility could be that the “real world” problems have special properties because the real world is very special, Tegmark said.

Take one of the biggest neural-network mysteries: These networks often take what seem to be computationally hairy problems, like the Go game, and somehow find solutions using far fewer calculations than expected.

It turns out that the math employed by neural networks is simplified thanks to a few special properties of the universe. The first is that the equations that govern many laws of physics, from quantum mechanics to gravity to special relativity, are essentially simple math problems, Tegmark said. The equations involve variables raised to a low power (for instance, 4 or less).

What’s more, objects in the universe are governed by locality, meaning they are limited by the speed of light. Practically speaking, that means neighboring objects in the universe are more likely to influence each other than things that are far from each other, Tegmark said.

Many things in the universe also obey what’s called a normal or Gaussian distribution. This is the classic “bell curve” that governs everything from traits such as human height to the speed of gas molecules zooming around in the atmosphere.

Finally, symmetry is woven into the fabric of physics. Think of the veiny pattern on a leaf, or the two arms, eyes and ears of the average human. At the galactic scale, if one travels a light-year to the left or right, or waits a year, the laws of physics are the same, Tegmark said.

All of these special traits of the universe mean that the problems facing neural networks are actually special math problems that can be radically simplified.

“If you look at the class of data sets that we actually come across in nature, they’re way simpler than the sort of worst-case scenario you might imagine,” Tegmark said.

There are also problems that would be much tougher for neural networks to crack, including encryption schemes that secure information on the web; such schemes just look like random noise.

“If you feed that into a neural network, it’s going to fail just as badly as I am; it’s not going to find any patterns,” Tegmark said.

While the subatomic laws of nature are simple, the equations describing a bumblebee flight are incredibly complicated, while those governing gas molecules remain simple, Lin added. It’s not yet clear whether deep learning will perform just as well describing those complicated bumblebee flights as it will describing gas molecules, he said.

“The point is that some ’emergent’ laws of physics, like those governing an ideal gas, remain quite simple, whereas some become quite complicated. So there is a lot of additional work that needs to be done if one is going to answer in detail why deep learning works so well.” Lin said. “I think the paper raises a lot more questions than it answers!”


Editor’s note: Original Source ‘LiveScience’

Tia Ghose. “The Spooky Secret Behind Artificial Intelligence’s Incredible Power”

LiveScience. N.p., Web. 7 October. 2016.