Dangers of Image Geo Tagging

What is Image Geo tagging anyways?

In short a geotag is a meta tag embedded into the attributes of a digital image.

Did you know today's smart phones and digital cameras embed hidden data into the photographs you take? The photos you take with your modern smart phone can tell others:

• Where you live
• Where you work
• Where you go to school
• Where you spend your free time
• Where your friends or family live
• When there is nobody home
• Where you park your car
• And the list goes on and on and on.....

Now this may not be a big deal if you are taking photographs of yourself or a friend in a public place like Lake Eola in Orlando Fl, Cranes Roost Park in Altamonte Springs Fl or another well known public place. On the other hand if you are taking photos in your home, at your job or any other place you don't want a stranger to know then you probably should continue reading this article.

How does it happen?

When you take a photograph with a smart phone or digital camera, it takes much more than just a photograph. Most of today's smart phones such as the Motorola DROID or the APPLE IPHONE have the ability and do so by default add GeoTags to the photographs you take which include information about the EXACT location where the photograph was taken, what date and time the photograph was taken and this poses a real security threat to consumers.

Let's pretend you take photos of yourself or your family or your friends with your APPLE iPhone, Motorola DROID or another modern smart phone. Now let's pretend you upload those photos to your Facebook, MySpace, a singles website or even email them to somebody you don't know very well.

Sounds pretty normal so far, right?

The hidden danger is anybody with the know-how or technical knowledge if you will can view the hidden data embedded in your photographs and see exactly where the photos were taken, when the photos were taken and much more...

How do you protect yourself?

You can turn off the GPS feature on your smart-phone, but you might still need the GPS feature turned on for GPS navigation. So if you want to protect yourself you would turn the GPS functionality off on your smart phone when you are taking photographs and turn the GPS function back on if you happen to need to use the GPS features in your smartphone.

 

Data Mining - A Short Introduction

Data mining is an integral part of data analysis which contains a series of activities that goes from the 'meaning' of the ideas, to the 'analysis' of the data and up to the 'interpretation' and 'evaluation' of the outcome. The different stages of the technique are as follows:

Objectives for Analysis: It is sometimes very difficult to statistically define the phenomenon we wish to analyze. In fact, the business objectives are often clear, but the same can be difficult to formalize. A clear understanding of the crisis and the goals is very important setup the analysis correctly. This is undoubtedly, one of the most complex parts of the process, since it establishes the techniques to be engaged and as such, the objectives must be crystal clear and there should not be any doubt or ambiguity.

Collection, grouping and pre-processing of the data: Once the objectives of the analysis are set and defined, we need to gather or choose the data needed for the study. At first, it is essential to recognize the data sources. Usually data are collected from the internal sources as the same are economical and more dependable and moreover these data also has the benefit of being the outcome of the experiences and procedures of the business itself.

Investigative analysis of the data and their conversion: This stage includes a preliminary examination of the information available. It involves a preliminary assessment of the significance of the gathered data. An exploratory and / or investigative analysis can highlight the irregular data. An exploratory analysis is important because it lets the analyst choose the most suitable statistical method for the subsequent stage of the analysis.

Choosing statistical methods: There are multiple statistical methods that can be put into use for the purpose of analysis, so it is very essential to categorize the existing methods. The choice statistical method is case specific and depends on the problem and also upon the type of information available.

Data analysis on the basis of chosen methods: Once the statistical method is chosen, the same must be translated into proper algorithms for working out the results. Ranges of specialized and non-specialized software are widely available for data mining and as such it is not always required to develop ad hoc computation algorithms for the most 'standard' purpose. However, it is essential that the people managing the data mining method well aware and have a good knowledge and understanding of the various methods of data analysis and also the different software solutions available for the same, so that they may adapt the same in times of need of the company and can flawlessly interpret the results.

Assessment and contrast of the techniques used and selection of the final model for analysis: It is of utmost necessity to choose the best 'model' from the variety of statistical methods accessible. The selection of the model should be based in contrast with the results obtained. When assessing the performance of a specific statistical method and / or type, all other dependent and / or relevant criterions should also be considered. The other criterions may be the constraints on the company both in terms of time and resources or it may be in terms of quality and the accessibility of data.

Elucidation of the selected statistical model and its employment in the decision making process: The scope of data mining is not limited to data analysis rather it is also includes the integration of the results so as to facilitate the decision making process of the company. Business awareness, the pulling out of rules and their use in the decision process allows us to proceed from the diagnostic phase to the phase of decision making. Once the model is finalized and tested with an information set, the categorization rule can be generalized. But the inclusion of the data mining process in the business should not be done in haste; rather the same should always be done slowly, setting out sensible and logical aims. The final aim of data mining is to be an integral supporting part of the company's decision making process.

 

Web Mining

With the bang of the era of information technology, we have entered into an ocean of information. This information blast is strongly based on the internet; which has become one of the universal infrastructures of information. We can not deny the fact that, with every passing day, the web based information contents are increasing by leaps and bounds and as such, it is becoming more and more difficult to get the desired information which we are actually looking for. Web mining is a tool, which can be used in customizing the websites on the basis of its contents and also on the basis of the user interface. Web mining normally comprises of usage mining, content mining and structure mining.

Data mining, text mining and web mining, engages various techniques and procedures to take out appropriate information from the huge database; so that companies can take better business decisions with precision, hence, data mining, text mining and web mining helps a lot in the promotion of the 'customer relationship management' goals; whose primary objective is to kick off, expand, and personalize a customer relationship by profiling and categorizing customers.

However, there are numbers of matters that must be addressed while dealing with the process of web mining. Data privacy can be said to be the trigger-button issue. Recently, privacy violation complaints and concerns have escalated significantly, as traders, companies, and governments continue to gather and warehouse huge amount of private information. There are concerns, not only about the collection and compilation of private information, but also the analysis and use of such data. Fueled by the public's concern about the increasing volume of composed statistics and effective technologies; conflict between data privacy and mining is likely to root higher levels of inspection in the coming years. Legal conflicts are also pretty likely in this regard.

There are also other issues facing data mining. 'Erroneousness of Information' can lead us to vague analysis and incorrect results and recommendations. Customers' submission of incorrect data or false information during the data importation procedure creates a real hazard for the web mining's efficiency and effectiveness. Another risk in data mining is that the mining might get confused with data warehousing. Companies developing information warehouses without employing the proper mining software are less likely to reach to the level of accuracy and efficiency and also they are less likely to receive the full benefit from there. Likewise, cross-selling may pose a difficulty if it breaks the customers' privacy, breach their faith or annoys them with unnecessary solicitations. Web mining can be of great help to improve and line-up the marketing programs, which targets customers' interests and needs.

In spite of potential hurdles and impediments, the market for web mining is predicted to grow by several billion dollars in the coming years. Mining helps to identify and target the potential customers, whose information are "buried" in massive databases and to strengthen the customer relationships. Data mining tools can predict the future market trends and consumer behaviors, which can potentially help businesses to take proactive and knowledge-based resolutions. This is one of the causes why data mining is also termed as 'Knowledge Discovery'. It can be said to be the process of analyzing data from different points of view and sorting and grouping the identified data and finally to set up a useful information database, which can further be analyzed and exploited by companies to increase and generate revenue and cut costs. With the use of data mining, business organizations are finding it easier to answer queries relating to business aptitude and intelligence, which were very much complicated and intricate to analyze and determine earlier