Security Ethical Implications Data Mining †Myassignmenthelp.Com

Question: Discuss About The Security Ethical Implications Data Mining? Answer: Introduction: Data mining is a process where patterns in large data sets are discovered by using methods of database management system, machine language and statistics. It is a sub section of computer science where the intended goal is the extraction of information from a given data set and transforming it to a simple language intended for future use. Data mining is the next step of analysis of the discovery of knowledge in database process. This report consists of the reason for requirements of data mining in business along with a recent example to support the reason. This report also includes the security, ethical and privacy problems of adopting data mining and some examples to support the statements. Discussion: Data mining in business: Data mining is a new and very powerful tool with a potential to help companies or business organizations aim towards the most important aspect about customer behavior and behavior of new clients. Data mining is a type of discovery of knowledge, which is a computer-operated process, which involves searching of large data sets and finding of patterns and meaning in those data sets (Larose, 2014). The tools used in data mining processes is used to predict the behaviors and trends in future which helps the company or business organizations involved to make good decisions. Companies or business organizations in almost every industries including finance, health, retail and production. By analyzing the data sets by pattern recognition technology and mathematical/statistical tools, data mining helps in identifying facts, relations or patterns. The detailed uses of data mining includes market segmentation which consists of characteristics of the customers, customer churn which depicts the loyalty of the customer, fraud detection which shows the likeliness of fraud transactions. It also includes direct marketing that allows the highest conversion rates in the market, interactive marketing, which depicts the interests of users accessing a website (Shmueli Lichtendahl 2017). In addition, market basket analyzing helps the companies or business organizations to understand the likeliness of products to be purchased together and trend analysis, which shows the difference in behavior in customers over a one-month gap. Data mining in business involves technologies that help to provide historical, current and predictable strategies that could be implied in the business. The common functions of data mining in business operation include online analytics, reporting, process mining, event processing, performance management, text mining and predictive analysis (Provost Fawcett, 2013). Data mining can help the decision makers in a company or business organization to make successful actions based on the information that is provided. It can also help the authorities to get information on competitor marketing, condition of the market or behavior of the consumers. Recent news article about data mining: According to chicagotribune.com, a recent news article was published in 2013, which showed collaboration between technical firms in Chicago with the venture capital of CIA ("CIA venture arm invests in Chicago-based maker of artificial intelligence technology", 2017). Stuart Frankel, the CEO of the startup claims to be very pleased with the portfolio and hopes that this will contribute to a market expansion of the firm. The name of the tech firm is Narrative Science in Chicago. For this collaboration, Narrative Science proposed the development of Quill, which is a technology that will help the intelligence agency identify large data sets like video surveillances, financial transaction and social media coverage. The intelligence algorithm of Quill will help to analyze enormous amounts of data and provide data based in English. The program can produce many types of formats, which ranges from tweets to business reports. The associated clients of Narrative Science include many industries like marketing or financial services. The news article also provides funny information about CIA Director David Petraeus saying that the technology provided by them is much greater than the technologies seen in most films (Goldman, 2015). In addition, they also have confirmed that the technology of removing finger prints or eyeball images are not present but are supposed to be under development. The link for this news article is - https://articles.chicagotribune.com/2013-06-06/business/ct-biz-0606-narrative-science-20130606_1_intelligence-community-in-q-tel-technology Implications: Data mining is used to get interesting patterns in data sets. The increasing implementation of data mining in nearly every companies or organizations has created enthusiasm for widespread adoption but on the same time, it has also increased risks and pressures of data information acquisition. Data mining has shown great results in cases of biomedical research and health. The early detection of epidemic outbreaks, detection of genomes or patterns of side effects by drug ingestion is the areas where data mining in big data has shown success ("Big Data, Human Rights and the Ethics of Scientific Research Opinion ABC Religion amp; Ethics (Australian Broadcasting Corporation)", 2017). However, the Snowden revelations, has shown that how the use of big data and data mining led to database hack and other cyber-crime which eventually led to undermining of trust, privacy, liberty and democracy. Privacy has become too complex due to the evolvement of data mining. Originally, data mining provided users to access information but with modernization, the impact has greatly increased (Xu et al., 2014). This gathering of personal information has caused the rise of many concerns in privacy. For example, data mining process can be used to get information of individuals like number, address, social security id, drivers license or e-mail. This has posed a great concern for aggregation of personal information of these individuals and segregation of these data to create user profiles, which can be used in both the government and commercial sectors. Security is another part where data mining is used. The information of individuals, which can provide security implication, is analyzed beforehand. Data mining also checks individuals with criminal activities to get insights and patterns of their work in criminal activities. It can also check whether dangerous terrorists are involved with any particular patterns of crime. Since, prediction of these activities are provided by data mining officials, careful requirements and analysis of the details is required before taking necessary procedure against an individual because it may happen that sometimes the data that is accrued might not have any link with the undertaken investigation. Ethics is considered good if there is reason involved but also an obligation if pursuing of information is required. For example, health care scientists who are engaged with big data are not considered for their self-interest research in terms of money or fame but by the acquisition of public materials, which is supposed to benefit people (Yoo et al., 2012). However, the use of these goods depends on the ethics implied. The right to privacy in the Universal Declaration of Human Rights is very unfamiliar with high potential (Turner, 2014). The right tells people to imply their rights of acting in any scientific inquiries and to benefit from them. The right to science allows favors participation of citizens in scientific works. In modern times, the development in technologies caused an increase in the number of citizens exercising their rights of participation in scientific works. In health records, sometimes people demand their rights to check for information from newly made surveys or equipments. These rights to science and privacy are international rights but are also given force by domestic or regional authorities. Significance in business: The collection of information by the use of data mining process has made the uses of it legit as well as prone to abuses ("Big data security problems threaten consumers' privacy", 2017). For example, if the use of prediction can be applied to know the condition of the weather at a future time, the more use of it will take place and this will invite security or privacy threats. Due to the number of people affected in by breaches in the system, it is becoming a great concern for data mining analysts. In 2014, the breach of Arkansas University system led affected 50,000 people. In that same year, information of 145 million people was breached from eBay. This has led to rethinking of implication of privacy and security to deal with the problems. For buyers and consumers, the requirement of increased security in terms and conditions, agreements and trust seals are required to be collected from the companies or organizations that are involved in the collection of big data. The requirement for more security measures like encryptions, detections of illegal access and corporate methods are being taken up in the companies or organizations involved which will promote the security and tighten the relationship with the consumers. The requirements for increased revenue are an important goal that is present in every business organization or companies. The need to deliver targeted advertising is achieved by tracking the moves and preferences of the customers involved by the use of data mining and big data. For example, the Personality Insights software of IBM helps to build a profile of an individual, which is based on their online activities (Junior Inkpen, 2017). These activities are told as advantages to the customers who will help them to see valuable results but this is only useful to the company or organization involved. For example, the insurance companies target users based on these data personalities. These concerns must be addressed as the power of data mining can be used to detect fraudulent activities and can provide many advantages (Provost Fawcett, 2013). The key to achieve the power of data mining is transparency of these processes while providing security and privacy concerns. The data handlers must provide valuable reasons of what data they are collecting and analyzing and they reason behind that. People are also needed to be educated about the storage and collection of these data and companies must give satisfactory explanations about the protection they provide to safeguard them which helps in building trust. Conclusion: Thus, it can be concluded from the report that there are vast uses of implementing data mining in business. Its implementation helps the business organizations or companies to get successful insights regarding customer behavior or market analysis. However, the risk it poses is very much and it is the responsibility of the involved organization or business to gather the necessary requirements to provide security in terms of privacy, security and ethics. This way the company can improve their relationship with the customers and can stay in business for a long period. References: Big data security problems threaten consumers' privacy. (2017).The Conversation. Retrieved 9 August 2017, from https://theconversation.com/big-data-security-problems-threaten-consumers-privacy-54798 Big Data, Human Rights and the Ethics of Scientific Research Opinion ABC Religion amp; Ethics (Australian Broadcasting Corporation). (2017).Abc.net.au. Retrieved 9 August 2017, from https://www.abc.net.au/religion/articles/2016/11/30/4584324.htm CIA venture arm invests in Chicago-based maker of artificial intelligence technology. (2017).tribunedigital-chicagotribune. Retrieved 9 August 2017, from https://articles.chicagotribune.com/2013-06-06/business/ct-biz-0606-narrative-science-20130606_1_intelligence-community-in-q-tel-technology Goldman, J. (Ed.). (2015).The Central Intelligence Agency: An Encyclopedia of Covert Ops, Intelligence Gathering, and Spies [2 volumes]: An Encyclopedia of Covert Ops, Intelligence Gathering, and Spies. ABC-CLIO. Junior, R. A. P., Inkpen, D. (2017, May). Using Cognitive Computing to Get Insights on Personality Traits from Twitter Messages. InCanadian Conference on Artificial Intelligence(pp. 278-283). Springer, Cham. Larose, D. T. (2014).Discovering knowledge in data: an introduction to data mining. John Wiley Sons. Provost, F., Fawcett, T. (2013).Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.". Provost, F., Fawcett, T. (2013).Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.". Shmueli, G., Lichtendahl Jr, K. C. (2017).Data Mining for Business Analytics: Concepts, Techniques, and Applications in R. John Wiley Sons. Turner, B. (2014). Universal Declaration of Human Rights.The Statesmans Yearbook: The Politics, Cultures and Economies of the World 2015, 8-10. Xu, L., Jiang, C., Wang, J., Yuan, J., Ren, Y. (2014). Information security in big data: privacy and data mining.IEEE Access,2, 1149-1176. Yoo, I., Alafaireet, P., Marinov, M., Pena-Hernandez, K., Gopidi, R., Chang, J. F., Hua, L. (2012). Data mining in healthcare and biomedicine: a survey of the literature.Journal of medical systems,36(4), 2431-2448.