8083 mod 5 assgn 2
RUNNING HEAD: CYBERSECURITY 1
CYBERSECURITY 2
Cyber security
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I have chosen cybersecurity as my security threat because it is an emerging trend and also affects the operations of many business organizations. Furthermore, (Ullah et al., 2019). notes that cybersecurity greatly interferes with personal information as most hackers tend to steal and sell personal information such as social security numbers. In the US, almost 5 business organizations usually lose their information to hackers daily. However, cybersecurity threats may result from both national and international hackers. Additionally, business organizations are taking advantage of cybersecurity by hiring hackers that steal information from their rivals. This helps them to understand the strengths and weaknesses of their rivals. As a result, most business organizations in the country employ people who have the knowledge and skills in cyber-crime to protect their personal information. Therefore, this is the reason why I selected this topic.
In exploring this threat, I used statistical software. The statistical software works by carrying out the statistics about a particular issue. For example, in cybersecurity, I used the software to analyze the level of cybersecurity in the US, UK, Russia, and China. The results showed that in all those countries, the level of cybersecurity is more than 20% (Ullah et al., 2019). This software can analyze millions and millions of documents to bring the desired results to the user. Additionally, I decided to use this software due to the nature of the information being evaluated. Cybersecurity is a very wide topic and to bring desired results, I used this software to get the desired information about hacking and security threats to personal information.
The use of statistical software has several advantages. First, it is easy and convenient to use, and therefore, it does not require any technical skills to use (Tweneboah-Koduah, Skouby, and Tadayoni, 2017). Most business organizations use this software daily since the users do not have to undergo training programs on how to use it. Secondly, this software is compatible with most computer systems and it does not require a lot of procedures to install. Thirdly, it works very fast and therefore, results are generated within a short period. This saves the time of the user who can conduct several types of research in an hour or a day. Gunduz and Das (2020) note that the software can be used to solve multiple tasks within a short period due to its flexibility and speed of operation.
However, there several privacy concerns with the use of statistical software. Hackers and information brokers are taking the advantage of this software to access and acquire personal information belonging to the citizens. Therefore, the integrity and privacy of the people’s information may not be guaranteed in the future (Tweneboah-Koduah, Skouby, and Tadayoni, 2017). In the US, for example, citizens are always required to give their social security numbers to get services. There have been cases of such information leaks to the internet and information brokers are taking advantage of statistical software to steal such information and sell it to unauthorized people for their benefits (Lind, Marchal, and Wathen, 2017). However, the benefits of statistical software outweigh the damages. Apart from conducting research, this software is also used by business managers to survey the market, and generate the results for effective decision making. The cases of information leaks have been rare and if the citizens and business organization secure their personal information, there is little chance for hackers and information brokers to get information using the software. However, if cases of information leak will increase in the future, there is a huge possibility of hackers using the software to access other people’s information. The future technology will provide a variety of means by which people can secure their personal information and hence, there will be little chances of information leak.
References
Gunduz, M. Z., & Das, R. (2020). Cyber-security on the smart grid: Threats and potential solutions. Computer networks, 169, 107094.
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2017). Statistical techniques in business & economics. McGraw-Hill Education.
Tweneboah-Koduah, S., Skouby, K. E., & Tadayoni, R. (2017). Cybersecurity threats to IoT applications and service domains. Wireless Personal Communications, 95(1), 169-185.
Ullah, F., Naeem, H., Jabbar, S., Khalid, S., Latif, M. A., Al-Turjman, F., & Mostarda, L. (2019). Cybersecurity threats detection in the internet of things using deep learning approach. IEEE Access, 7, 124379-124389.