Emerging threats to business security

Now more than ever, businesses need to be concerned about the security of their networks. The
number, variety and strength of the threats to computer and network security have dramatically increased and businesses need to be prepared against an ever-changing landscape of malware attacks. Traditional security providers are focused on protecting computer applications. While this is certainly still important, today’s biggest threats – as well as the most prominent emerging threats – are targeted at the emerging online lifestyle. With computer literacy increasing dramatically and the line between private and business use of computers and networks blurring, businesses need to keep a close eye on their employee’s activities on their company networks and ensure that their network security is not at stake.

In 2007, malware became one of the leading threats to network security. Malware is in constant flux and the only discernible trend right now is toward creating variants on existing pieces of malware, with ever-improving stealth capabilities and using them in more targeted attacks. There are numerous documented cases recently of targeted malware attacks against businesses (usually employing infected MSOffice files, though other techniques were also used). In each case, the malware used was written specifically for the occasion and saw little spreading beyond the initially-affected companies. As malware continues its surprise attacks, businesses should be on guard, especially as malware becomes increasingly sophisticated and continues to strike where businesses thought they were safe. An area of significant concern for increasing malware attacks is in mobile devices. The use of smartphone technology has played a pivotal role in the threat's transition from multifunction, semistationary PCs to palm-sized "wearable" devices. The recent trend towards providing mobile devices with web browsers and always-on internet access has brought all the security concerns of the web to the mobile world and their connected enterprises. Viruses based on browser exploits will become common. As capabilities expand, security is traded for functionality, giving rise to a whole new class of opportunities for malicious attacks. Much like viruses on a computer, viruses on mobile devices can delete files, infect files, send private information from the mobile device, facilitate external attacks and/or drain the battery.

Can Neural Networks be useful for Business?

Neural Networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice. Their use for risk assessment is also growing and they have been employed to visualise complex databases for marketing segmentation. This boom in applications covers a wide range of business interests — from finance management, through forecasting, to production. The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise.

Neural Networks are being used increasingly in business applications, and in certain fields, such as fraud detection, they have become the norm. Prime applications of neural networks include finance management, production, operations, and business forecasting. NeuroXL Predictor and Classifier increase the range of applications even further by being easy-to-use, well integrated with Microsoft Excel, and requiring no knowledge of neural networks to perform complex classifications and predictions. All the analyst needs to do is specify the inputs and set a few parameters - the applications then quickly determine the optimum solution to the problem.

Advanced Technology for Prediction and Classification

Neural networks are a well-established technology for solving prediction and classification problems, using training and testing data to build a model. The data involves historical data sets containing input variables, or data fields, which correspond to an output. Using the training data, the network "learns" the solution to a problem.

The way neural networks process information is similar to the way the human brain works. The network is composed of a large number of highly interconnected processing elements (neurons) that work in parallel to solve the problem. The networks learn by example, and thus do not require complex rules to work.

NeuroXL Classifier and Predictor as tools for Business Analysts

NeuroXL Classifier and Predictor have become quite popular with business analysts, having proven their classification powers through comparison with other applications and techniques. Using either application, all the user needs to do is specify the inputs and outputs and set the required parameters - the applications do the rest of the work of training the data and generating a prediction or classification.

NeuroXL Classifier and Predictor are both powerful, easy-to-use and affordable solutions for advanced classification of simple and complex data. Both are designed as add-ins to Microsoft Excel, are easy to learn and do not require that data be exported out of or imported into Excel. Both applications can be applied to a wide variety of business disciplines, including:

• Industrial process optimization.
• Loan approvals.
• Credit scoring.
• Marketing campaign prediction.
• Cost prediction.

Workings of Algorithms

Genetic Algorithm is an effective method for solving a problem using a finite sequence of instructions. Algorithms are used for calculation, data processing, and many other fields.

Genetic Alogrithms are adaptive search techniques that can learn high performance knowledge structures. The genetic algorithms' strength comes from the implicitly parallel search of the solution space that it performs via a population of candidate solutions and this population is manipulated in the simulation. The candidate solutions represent every possible behaviour of the robot and based on the overall performance of the candidates, each could be assigned a fitness value. Genetic operators could then be applied to improve the performance of the population of behaviours. One cycle of testing all of the competing behaviour is defined as a generation, and is repeated until a good behaviours is evolved. The good behaviour is then applied to the real world. Also because of the nature of GA, the initial knowledge does not have to be very good.

Before you can use a genetic algorithm to solve a problem, a way must be found of encoding any potential solution to the problem. This could be as a string of real numbers or, as is more typically the case, a binary bit string.

At the beginning of a run of a genetic algorithm a large population of random chromosomes is created. Each one, when decoded will represent a different solution to the problem at hand. Let's say there are N chromosomes in the initial population.
Then, the following steps are repeated until a solution is found:

Test each chromosome to see how good it is at solving the problem at hand and assign a fitness score accordingly. The fitness score is a measure of how good that chromosome is at solving the problem to hand.

Select two members from the current population. The chance of being selected is proportional to the chromosomes fitness. Roulette Wheel selection is a commonly used method.

Dependent on the crossover rate crossover the bits from each chosen chromosome at a randomly chosen point.

Step through the chosen chromosomes bits and flip dependent on the mutation rate.

Repeat step 2, 3, 4 until a new population of N members has been created.

Basically its a simple way of finding a solution to a problem that physically doing would take hours/days/weeks etc. Like how does the GPS system know which journey is the shortest... Algorithms. Trying to work out the distance yourself would take a long time.

Risk Management

Todays lecture was a bit different. It still had a theme of course: Risk Management. But the layout of the lecture was somewhat different. Basically the week before we were told that what our lecturer had in mind for next wks lecture would need 3 hours to complete.

So what exactly was our 3 hour lecture about...

Well our lecturer demonstrated to us a robot that when a ball was placed in front of it, the robot would go towards the ball and attempt to grab it and when the lecturer clapped his hands released the ball and turned around back and went back to the lecturer.

Pretty cool right? Totally. That is until he informs us that he would like us to recreate exactly what he did. Which means the build the robot (lego style), the stand the legos on, the ball and stand for the ball, and o ya program the robot to be able to do all that. Ok I'm exaggerating a bit. We were given instructions for building the robot and software to help us program the robot.

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We were also given 16 chips (our budget). Our lecturer said that he will be our consultant and that for every 15 mins we haven't got each of the stages completed he will take coin off us. What we didn't know was that each time he came around and we weren't paying attention to him he'd take more money that he should.
Lesson being you have to be alert and have your eye on everything or You Will Get Shafted.

It was a pretty good lecture. Showed us how to work in a team, delegate, budgeting and of course the risks involved if you don't have proper structure.

Artificial Intelligence

Right so Artificial Intelligence...
Every-one kind of has an idea of AI mostly because of the movie. You know the one with the cute kid from Sixth Sense and he's a robot or something. I don't know to be honest I never saw it. So probably a bad example.
Ok so the history of AI is what we were learning in class.
Right so AI is defined (by glorious wiki) as the intelligence of machines and the branch of computer science which aims to create it. Textbooks define the field as "the study and design of intelligent agents,"where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."

ok so to start the history of AI

1956 John McCarthy coins the phrase "artificial intelligence" at a conference at Dartmouth College, New Hampshire

Unimate, the first industrial robot

Shakey, the first movable robot

HAL 9000 from the movie 2001

1956 Stanislaw Ulam develops Maniac I, the first chess program to beat a human player, at the Los Alamos National Laboratory

1961 UNIMATE is the first industrial robot

1962 the term "personal computer" appeared in a November 3, 1962 New York Times article reporting John W. Mauchly's vision of future computing

1965 Herbert Simon predicts that "by 1985 machines will be capable of doing any work a man can do"

1966 Joseph Weizenbaum, a computer scientist at the Massachusetts Institute of Technology, develops Eliza, the world's first chatbot

1968 Arthur C. Clarke writes "2001: A Space Odyssey" featuring HAL 9000, the artificial intelligence on-board computer of the spaceship

1969 Shakey, a robot built by the Stanford Research Institute in California, combines locomotion, perception and problem solving

Dante II and II

R2-D2 and C-3PO

1975 John Holland describes genetic algorithms in his book Adaptation in Natural and Artificial Systems

1977 Apple II, the first popular microcomputer manufactured by Apple Computer. It had color and high-resolution graphics

1977 The robots R2-D2 and C-3PO are an important part of the Starwars movies

1979 VisiCalc,the first spread-sheet starts the use of personal computers in the office. It was available on the Apple II

1979 A computer-controlled autonomous vehicle called the Stanford Cart, built by Hans Moravec at Stanford University, successfully negotiates a chair-filled room

1981 the IBM PC starts the "IBM PC compatible hardware platform". Based on these specifications (e.g. CGA graphics) it was possible to buy compatible components from other manufacturers. This started a wave of innovations. The operating system was PC-DOS from Microsoft, who purchased the earlier CP/M. The system was character based

1982 The Japanese Fifth Generation Computer project to develop massively parallel computers and a new artificial intelligence is born

Mid-1980s Neural networks become the new fashion in AI research

1992 Doug Lenat forms Cycorp to continue work on Cyc, an expert system that's learning common sense

1986 Honda Motor Company starts the line of humanoid robots ASIMO

1993 Dante I and II were walking robots used to explore live volcanoes

Roomba from iRobot

AIBO from Sony

ASIMO from Honda

1997 The Deep Blue chess program beats the then world chess champion, Garry Kasparov

1997 Microsoft's Office Assistant, part of Office 97, uses AI to offer customised help

1999 Sony introduces Aibo, a robotic dog capable of seeing, walking and interacting with its environment, sold as a toy.

1999 Remote Agent, an AI system, is given primary control of NASA's Deep Space 1 spacecraft for two days, 100 million kilometres from Earth

2001 The Global Hawk uncrewed aircraft uses an AI navigation system to guide it on a 13,000-kilometre journey from California to Australia

2002 ROOMBA, a robotic vacuum cleaner by iRobot, a company concentrating on robots for household work and military tasks

2004 In the DARPA Grand Challenge to build an intelligent vehicle that can navigate a 229-kilometre course in the Mojave desert, all the entrants fail to complete the course

2005 Several driverless vehicle manage to complete the course in the required time frame

And there you have it the story so far. A bit scary how influencial AI is and how necessary it is. Pretty exciting though. To see how much it has progressed in the past 40 years to imagine where we will be in another 40 years, it's going to be a different world I say.

Social Networking Sites for businesses - Hype? or Useful?

Sorry those links again are:

Patricks Bar:
http://www.facebook.com/profile.php?id=100000071358759&ref=ts

20 useful sites for businesses
http://www.sitepoint.com/blogs/2009/07/28/social-networking-sites-for-business/

Social Networking Sites for businesses - Hype? or Useful?

I think everyone at this stage knows what social networking is. But for those few that have been locked in a cupboard with a blackboard and some chalk for some 5 or so years, I'll kindly explain it to you.
Social Networking is a medium where a community of people with common interest/ideas can get together and communicate with one another over the internet.

Commonly used social networking sites would be:
Bebo (an area where you can connect with friends, put up pictures, blog, vlog. Common with teenagers, "young adults")
Facebook (similar to Bebo, but seen as an older version)
Flikr (photo-sharing network)
MySpace (same idea as Bebo or Facebook but my common with artists, particularly up and coming artists who wants to use the site as a way to get their music across to potential fans)
To be honest the list is pretty much endless. Any interest you have you will pretty much be able to find a site with like minded people.

Back to my reason for blogging.
Is this a good place for businesses to manipulate?

For advertising I think so... With the likes of bebo and even facebook where the demographic is primarily young students, then advertising your company if you are a bank or clothes shop is a very good idea.

But what I'm really talking about is companies that set up their own page in these social networking sites.

If you look at MySpace... this is a great place for new artists to get their music across. Lily Allen became well known because of her MySpace. She couldn't get a record deal and therefore starting putting up vlogs of her singing songs and got the biggest response in MySpace history. And the rest as they say is history. This was a great business idea for Lily and is the primary reason for she is today.
Definitely not hype.

In the area of pubs and clubs. I myself have both a bebo and facebook account (though if I'm honest the bebo account is pretty redundant these days). But with facebook loads of pubs and clubs back home have their own facebook page. I personally think this is a great idea because with Facebook if you're friends with these pubs and clubs you automatically get details of whatever they're talking about.
EG http://www.facebook.com/profile.php?id=100000071358759&ref=ts
The link shown above is for Patricks Bar, a new bar opening in Ennis, it used to be called Moscos. Anyway they're opening their doors this coming friday 09/10. Considering they are a new pub with a brand new name, so not that well known, most of their future customers will be students or people who're working outside the town and therefore will not hear the news of the bar opening. So what do they do? They go onto the pages of other bars in the town find their friends, and ask them to be their friends. Which happened to me. I got a request from Patricks Bar to be my friend. So whenever Patricks Bar makes a new post about when they're opening or new promotions, when I log onto my page I will see their news. Therefore I will know Patricks Bar is opening on Friday. Free publicity. What's so wrong with that?
In that case, its definitely not hype.

I think for businesses to get ahead they have accept that this is the way of the future and therefore have to get on board. Social networking sites aren't just fun childlike sites like bebo and facebook. There are social networking sites available for business minds
EG http://www.sitepoint.com/blogs/2009/07/28/social-networking-sites-for-business/
This link shows a list of social networking sites focused on business users and meeting their needs. Showing there is a place for everyone.

Therefore social networking for businesses is definitely not hype. You just have to know how to work it to your advantage is all.