Data Mining and Large Scale Data Queries

In recent history technology has become more and more integrated into everyday life and unfortunately old privacy standards are not keeping up. More specifically as technology users become more connected and reliant on these devices they tend to overlook the fact that these networks they are using to stay connected have the ability to collect and distribute user information. This idea can be more commonly referred to as data mining, or the collection and sorting of large amounts of data searching for specific bits of information. What this means for users is that any time they input information or visit different areas online these movements can be tracked and used to create data for the data miners.

In the article by Ling and Luckin we see that social justice can be applied to many different groups for a variety of reasons and users of these technologies are no different. Most of the people using these devices such as phones, tablets, and computers are usually in the dark about a lot of these tracking systems as they are not generally spoken about or out in the open at all. This can lead to unwanted consequences stemming from the “trail of breadcrumbs” users are leaving.

One of the easiest and simplest applications used to combat some of the effects of data mining is a Virtual Private Network (VPN). Essentially this application works to encrypt any data transfers the user makes as they make their way through different networks working to remove any private information that could be found in large scale data mining searches. One of the major culprits of this are the “cookies” that are automatically downloaded from various websites containing information about the different aspects of the users visit including personal information entered (Stretton, T. & Aaron, L.). Yet the major downside to these sorts of applications is that without the user actively using these technologies which generally aren’t as streamlined and user friendly they choose to avoid using them altogether. Without the encryption of data it makes it incredibly easy for data miners to write specific algorithms to rapidly sort through data and mark specific bits that are defined by the algorithm being used (Ostrovsky, R. & Skeith, W.).

One of the larger areas of concern for data mining is generally the healthcare field as the amount of information provided to most healthcare providers is not only very sensitive information but also very expansive. This is only made more invasive with the increasing ability to take care of most data entry through online networks via mobile devices. In fact well over 70 million Americans alone have some form of medical history/information in an electronic format. (Motiwalla, L & Li, X). This number is from a poll prior to the introduction of national healthcare and as such has almost certainly increased a large amount. As these statistics help show, data mining can prove to be a very invasive practice and steps should be taken to thwart these acts. VPNs are not a “one trick pony” and cannot do anything to stop those who have already received access to this information from using it for their own benefit but it help to prevent a greater amount of personal information escaping into public hands.

Works Cited

Motiwalla, L., & Li, X. (2010). Value Added Privacy Services for Healthcare Data. Services, 64-71. Retrieved February 13, 2015, from http://ieeexplore.ieee.org.libproxy.temple.edu/xpls/icp.jsp?arnumber=5575776#authors

Ostrovsky, R., & Skeith, W. (2010). Private Searching on Streaming Data. Journal of Cryptology, 20(4), 397-430. Retrieved February 13, 2015, from http://link.springer.com.libproxy.temple.edu/article/10.1007/s00145-007-0565-3

Stretton, T., & Aaron, L. (2015). The dangers in our trail of digital breadcrumbs. Computer Fraud and Security, 13-15. Retrieved February 13, 2015, from http://ac.els-cdn.com.libproxy.temple.edu/S1361372315700060/1-s2.0-S1361372315700060-main.pdf?_tid=4ec48830-b570-11e4-95e3-00000aab0f26&acdnat=1424045649_abe0fba692dff5f48d8d3ea28ae629ee

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