Data Classification Schemes
Name
Institution
Assignment
Locating Harvard University’s classification scheme was not very difficult. I found it during my first search. I just typed “Harvard University classification scheme” on Google, and the first result contained the information I was looking for. I believe that finding the university’s classification scheme was easy because it wants the public, including potential students, to be aware that it takes stringent measures to protect sensitive information. This way, it succeeds in gaining the public trust of its capabilities as a learning institution (Seetha, Murty & Tripathy, 2017).
Legally protected information, or what is referred to as ‘High-Risk Confidential Information’ (HRCI) at Harvard (for example, SSNs, health information, credit card numbers, etc), needs a high degree of protection, whereas lower risk data (for example, information available to the public), needs proportionately less protection (Harvard University, 2020). In this regard, Harvard University has come up with a classification scheme that relates directly to data sensitivity. For example, public data or data that is not confidential is classified as Level 1. In contrast, data that is under the protection of the law and data that is perceived to be of the highest risk is classified as Level 5 (Harvard University, 2020). These classification levels do not differ that much from other industries. This is because other industries also tend to categorize data based on its sensitivity.
The types of data classified in each industry appear to be the same. This is because examples of sensitive information across industries are similar: social security numbers, information related to healthcare, credit card numbers, bank account details, and passport information. (Shabtai, Elovici & Rokach, 2012). Therefore, industries tend to ensure that these kinds of information are highly protected compared to non-sensitive information (Fernando, 2019). In this regard, I believe that the types of data should be the same for each kind of organization.
References
Fernando, A. C. (2019). Corporate governance: Principles, policies and practices. Pearson Education India.
Harvard University. (2020). Data Classification. Retrieved from https://its.gse.harvard.edu/information-security/data-classification#:~:text=The%20University%20has%20defined%20a,considered%20of%20the%20highest%20risk.
Seetha, H., Murty, M., & Tripathy, B. (2017). Modern technologies for big data classification and clustering. IGI Global.
Shabtai, A., Elovici, Y., & Rokach, L. (2012). A survey of data leakage detection and prevention solutions. Springer Science & Business Media.
