Confidentiality Essays (Examples)
Study Document
Hand Hygiene And Infection In Hospitals
… all of the study participants were given the assurance that any data and information rendered would be handles with the highest level of confidentiality.
4. Describe one strength and one limitation of the study
A key strength of the study is that there exists a limited literature ……
References
References
Joshi, S. C., Diwan, V., Tamhankar, A. J., Joshi, R., Shah, H., Sharma, M., ... & Lundborg, C. S. (2012). Qualitative study on perceptions of hand hygiene among hospital staff in a rural teaching hospital in India. Journal of Hospital Infection, 80(4), 340-344.
Tan Jr, A. K., & Jeffrey Olivo, B. S. (2015). Assessing healthcare associated infections and hand hygiene perceptions amongst healthcare professionals. International Journal of Caring Sciences, 8(1), 108.
Study Document
Cyber Espionage
… knowledge and expertise on the phenomenon being studied. Some of the potential ethical issues that could emerge include privacy of research participants and confidentiality. These issues will be addressed through ensuring participation is voluntary and participants will not be required to provide any personal identification information. Additionally, ……
References
Bibliography
Agarwal A. & CERT-IN. “Cyber Espionage, Infiltration and Combating Techniques.” Indian Computer Emergency Response Team, 2013. https://www.cert-in.org.in/Downloader?pageid=5&type=2&fileName=CIPS-2013-0128.pdf
Banks, W.C. “Cyber Espionage and Electronic Surveillance: Beyond the Media Coverage.” Emory law Journal 66, (2017).
Georgieva, I. “The Unexpected Norm-Setters: Intelligence Agencies in Cyberspace.” Contemporary Security Policy (2019).
Hjortdal, M. “China’s Use of Cyber Warfare: Espionage Meets Strategic Deterrence.” Journal of Strategic Security 4, no. 2 (2011).
Libicki, M. “The Coming of Cyber Espionage Norms.” 9th International Conference on Cyber Conflict, 2017. https://ccdcoe.org/uploads/2018/10/Art-01-The-Coming-of-Cyber-Espionage-Norms.pdf " target="_blank" REL="NOFOLLOW">
Study Document
Privacy In Social Networks Regarding Machine Learning
...Confidentiality Abstract
This paper discusses the issue of privacy in social networks with respect to advances in machine learning. It shows how machine learning protocols have been developed both to enhance and secure privacy as well as to invade privacy and collect, analyze, predict data based on users’ information and experience online. The conflict between these two directions in machine learning is likely to lead to a system wherein machine learning algorithms are actively engaged in the subversion of one another, with one attempting to conceal data and the other attempting to uncover it. This paper concludes with recommendations for social networks and the issue of privacy regarding machine learning.
Introduction
Social networks have allowed an ocean of personal data to form that is now sitting there waiting for machine learning algorithms to collect it, analyze it, and recognize individuals on social media (Oh, Benenson, Fritz & Schiele, 2016). Machine learning……
References
References
Balle, B., Gascón, A., Ohrimenko, O., Raykova, M., Schoppmmann, P., & Troncoso, C. (2019, November). PPML\\\\\\\\\\\\'19: Privacy Preserving Machine Learning. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (pp. 2717-2718). ACM.
Bilogrevic, I., Huguenin, K., Agir, B., Jadliwala, M., Gazaki, M., & Hubaux, J. P. (2016). A machine-learning based approach to privacy-aware information-sharing in mobile social networks. Pervasive and Mobile Computing, 25, 125-142.
Bonawitz, K., Ivanov, V., Kreuter, B., Marcedone, A., McMahan, H. B., Patel, S., ... & Seth, K. (2017, October). Practical secure aggregation for privacy-preserving machine learning. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (pp. 1175-1191). ACM.
Hunt, T., Song, C., Shokri, R., Shmatikov, V., & Witchel, E. (2018). Chiron: Privacy-preserving machine learning as a service. arXiv preprint arXiv:1803.05961.
Lindsey, N. (2019). New Research Study Shows That Social Media Privacy Might Not Be Possible. Retrieved from https://www.cpomagazine.com/data-privacy/new-research-study-shows-that-social-media-privacy-might-not-be-possible/
Mohassel, P., & Zhang, Y. (2017, May). Secureml: A system for scalable privacy-preserving machine learning. In 2017 IEEE Symposium on Security and Privacy (SP) (pp. 19-38). IEEE.
Mooney, S. J., & Pejaver, V. (2018). Big data in public health: terminology, machine learning, and privacy. Annual review of public health, 39, 95-112.
Oh, S. J., Benenson, R., Fritz, M., & Schiele, B. (2016, October). Faceless person recognition: Privacy implications in social media. In European Conference on Computer Vision (pp. 19-35). Springer, Cham.
Study Document
Application Of Quality And Safety Concepts
… sharing of patients is ineffective and time-consuming, as well as puts patient data in jeopardy (i.e., risk of data leaks and loss of confidentiality/ privacy). Inefficient or partial information interchange may be highly dangerous if the patient requires complex or emergency treatment.
Hence, this paper holds that ……
References
Bibliography
Alotaibi, Y. K., & Federico, F. (2017). The impact of health information technology on patient safety. Saudi Med J, 38(12), 1173–1180.
Amit, M. (2019, January 28). 5 Problems Which Healthcare Technology Can Solve for a Healthier World. Retrieved from Net Solutions: https://www.netsolutions.com/insights/5-healthcare-problems-which-digital-technologies-can-solve-for-a-fit-and-healthy-world/
DeSanctis, G., & Poole, M. S. (1994). Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory. Organization Science, 5(2), 121-147.
Feldman, S. S., Buchalter, S., & Hayes, L. W. (2018). Health Information Technology in Healthcare Quality and Patient Safety: Literature Review. JMIR Med Inform, 6(2).
Halamka, J., Mandl, K., & Tang, P. (2008). Early Experiences with Personal Health Records. Journal of the American Medical Informatics Association, 15(1), 1-7.
IOM. (1999). To Err is Human: Building a Safer Health System. National Academy of Sciences.
Singh, H., & Sittig, D. (2016). Measuring and improving patient safety through health information technology: The Health IT Safety Framework. BMJ Quality & Safety, 25, 226-232.
Weigel, F., Hall, D. J., & Landrum, W. H. (2009). Human/Technology Adaptation Fit Theory for Healthcare. SAIS 2009 Proceedings.
Study Document
Cyber Espionage
… knowledge and expertise on the phenomenon being studied. Some of the potential ethical issues that could emerge include privacy of research participants and confidentiality. These issues will be addressed through ensuring that participation is voluntary. P and participants will not be required to provide any personalpersonally identifiable ……
References
Bibliography
Agarwal A. & CERT-IN. “Cyber Espionage, Infiltration and Combating Techniques.” Indian Computer Emergency Response Team, 2013. https://www.cert-in.org.in/Downloader?pageid=5&type=2&fileName=CIPS-2013-0128.pdf
Banks, W.C. “Cyber Espionage and Electronic Surveillance: Beyond the Media Coverage.” Emory law Journal 66, (2017).
Georgieva, I. “The Unexpected Norm-Setters: Intelligence Agencies in Cyberspace.” Contemporary Security Policy (2019).
Hjortdal, M. “China’s Use of Cyber Warfare: Espionage Meets Strategic Deterrence.” Journal of Strategic Security 4, no. 2 (2011).
Libicki, M. “The Coming of Cyber Espionage Norms.” 9th International Conference on Cyber Conflict, 2017. https://ccdcoe.org/uploads/2018/10/Art-01-The-Coming-of-Cyber-Espionage-Norms.pdf " target="_blank" REL="NOFOLLOW">
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