Monday, November 30, 2009

New & 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...”


So what is Information Security? Information Security can be defined as the protection of information systems against unauthorized access or modification and against denial of service to authorized users or the provision of service to unauthorized users.


So what new emerging security threats face businesses? Regardless of location or size all business conducts work on the internet and therefore they need to be aware of malware (malicious code) and attacks they are faced with in order to prevent their systems/network from being attacked. Traditional security providers such as MacAfee are focused on protecting computer applications. This is very important; however, it is not enough businesses need to keep a close eye on their employees’ activities on their computer networks. Today’s biggest threats are targeted at the emerging online lifestyle along with the most prominent emerging threats (viruses, worms etc.).

Malware is code installed without the permission or knowledge of the user (employees in the business) such as viruses, Trojans, logic bombs, worms and so on. Two years ago, Malware became one of the leading threats to network security. There have been a number of cases of targeted malware attacks against businesses which usually employ infected MS Office files. However, other techniques were used but this was the most common. As malware continues to grow and attacks become more sophisticated, businesses should be aware of all the possible attacks and how to prevent them and employees should know what to do in the event of an attack.

Mobile Devices is an area of concern for malware attacks. Security risks rise within business with the use of mobile devices. When using mobile devices businesses need to think smart and choose a mobile device with the best built in security controls and put a policy in place to only allow those devices on the network. The device should b e capable of encrypting stored information (providing you have chosen a device with good built in security controls). Each device should require authorisation and employers should ensure that passwords are strong passwords, strong passwords are easy to remember (therefore they don’t need to be recorded) but hard for an attacker to guess. Mobile devices should have the ability to remotely disable in case they are stolen or misplaced. Third party applications must be controlled on device platforms. Firewalls should be put in place to control the types of data that can be accessed in order to limit the exposure. Traffic should be tracked on mobile devices to look for attacks, use intrusion prevention software. Employees should be told to disable Bluetooth when they are not using it.

There are many more security threats facing businesses, especially as they grow with the use of new technologies. Businesses need to be aware of new and existing threats such as spyware, Trojans, worms, spam mail, phishing and many more. Every business should consider security integrated solutions which can be deployed and managed. Organisations can’t rely on basic network security anymore as the threats facing them are more sophisticate so therefore the security of the company needs to be more sophisticated. The security integrated in the organisation should be able to proactively determine where future threats are likely to arise and to ensure the whole network is secured.

Wednesday, November 25, 2009

Can Neural Networks be useful for Business?


“Neural networks do not perform miracles. But if used sensibly they can produce some amazing results.”


In information technology, a neural network (NN, ANN) is a system of programs and data structures that approximates the operation of the human brain. They are biologically inspired. A neural network usually involves a large number of processors operating in parallel, each with its own small sphere of knowledge and access to data in its local memory. Typically, a neural network is initially "trained" or fed large amounts of data and rules about data relationships.



Networks provide significant benefits in business applications. Neural networks are now globally recognized as the most effective and appropriate artificial intelligence technology for pattern recognition and as a result, they are actively being used for such applications as bankruptcy prediction, predicting costs, forecasting revenue, supporting commercial gaming and processing documents or images electronically. They solve “real world” problems in business and engineering.


In order for neural networks to solve “real world” problems they must be fed information. They require correct data pre processing, correct architecture selection and correct network training. Neural networks have many components (input layers, hidden layer, output layer, connections/arcs, weights, activation functions, training set and learning) and in order for neural networks to be successful they require proper user skills. The user must be familiar with and understand all the components. Most failures in neural networks in the past have come from improper user skills in appropriate preparation of data and design of a neural network. Nowadays, business benefits of neural technology are highly underestimated still due to difficulties in appropriate data pre-processing and network construction.


I have already briefly mentioned some of the benefits of neural networks in the business environment. The question is “Can Neural Networks be useful for business?”
After attending my lectures, studying the lecture slides and after my research I think Neural Networks are extremely useful for businesses and below I have listed why I think this.



Detection of medical phenomena


A variety of health-related indices, for example, a combination of heart rate, levels of various substances in the blood, respiration rate can be monitored. The onset of a particular medical condition could be associated with a very complex (e.g., nonlinear and interactive) combination of changes on a subset of the variables being monitored. Neural networks have been used to recognize this predictive pattern so that the appropriate treatment can be prescribed.



Stock market prediction
Here is another example; a complex, multidimensional example of how neural networks are used in reality is in the fluctuations of stock prices and stock indices. In some circumstances, neural networks are being used by many technical analysts to make predictions about stock prices based upon a large number of factors such as past performance of other stocks and various economic indicators.



Credit assessment


A variety of pieces of information are usually known about an applicant for a loan. For instance, the applicant's age, education, occupation, and many other facts may be available. After training a neural network on historical data, neural network analysis can identify the most relevant characteristics and use those to classify applicants as good or bad credit risks.

‘’Neural networks have extremely powerful predictive capabilities, designed to notice anomalies in spending behaviour which could signal unauthorized card use. Suspicious transactions can be identified as they enter the payment system at the authorization stage, allowing your card issuer to quickly alert you of possible fraud -- often stopping thieves in their tracks.’’ Visa



Monitoring machinery


Neural networks can be beneficial for businesses for cutting costs by bringing additional expertise to scheduling the preventive maintenance of machines. With training, neural networks can distinguish between the sounds a machine makes when it is running normally ("false alarms") compared to when it is on the verge of a problem. After this training period, the expertise of the network can be used to warn a technician of an upcoming breakdown, before it occurs and causes costly unforeseen "downtime”, saving time and money for the business. Time is money!



Engine management


Neural networks have been used to analyze the input of sensors from an engine. The neural network controls the various parameters within which the engine functions, in order to achieve a particular goal, such as minimizing fuel consumption.

There are many more interesting facts about neural networks. The following are some interesting websites I came upon while doing my research