ADS Capstone Chronicles Revised

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Donadel, A. (2023, September 28). This data breach has compromised nearly 900 institutions. University Business. https://universitybusiness.com/in-just-3-mont hs-this-data-breach-has-compromised-nearly 900-institutions/ Ersinesen, A. (2023). Discovery, classification, and protection of PII: Current state, problems, solution proposals. Journal of Privacy and Security, 15(2), 127–142. https://medium.com/@ersinesen/discovery-cl assification-and-protection-of-pii-current-stat e-problems-and-solution-proposals-3627e16f 2d8b Holmes, L., Crossley, S., Baffour, P., King, J., Burleigh, L., Demkin, M., Holbrook, R., Reade, W., & Howard, A. (2024). The Learning Agency Lab - PII data detection. Kaggle. https://kaggle.com/competitions/pii-detection -removal-from-educational-data Kulkarni, P., & Cauvery, N. K. (2021). Personally Identifiable Information (PII) Detection in the Unstructured Large Text Corpus using Natural Language Processing and Unsupervised Learning Technique. International Journal of Advanced Computer Science & Applications (Online), 12(9). https://doi.org/10.14569/ijacsa.2021.0120957 Nowicki, J., & Young, C. (2020, October 15). Data security: Recent K-12 data breaches show that students are vulnerable to harm. U.S. Government Accountability Office. https://www.gao.gov/products/gao-20-644Po ornima, K., & Cauvery, N. K. (2021). Personally identifiable information (PII) detection in the unstructured large text corpus using natural language processing and unsupervised learning technique. International Journal of Advanced Computer Science and Applications, (12)9, 508–517. https://thesai.org/Downloads/Volume12No9/

Paper_57-Personally_Identifiable_Informatio n_PII_Detection.pdf Prakash, P. (2020, March 18). Extend named entity recogniser (NER) to label new entities with spaCy. Towards Data Science. https://towardsdatascience.com/extend-name d-entity-recogniser-ner-to-label-new-entities with-spacy-339ee5979044 Ratinov, L., & Roth, D. (2009). Design challenges and misconceptions in named entity recognition. In S. Stevenson & X. Carreras (Eds.), Proceedings of the thirteenth conference on computational Natural language learning ([CoNLL-2009]; pp. 147–155). https://aclanthology.org/W09-1119 Roy, S., & Mitra, M. (2018). Identification and processing of PII data, applying deep learning models with Improved accuracy and efficiency. Saluja, B., Kumar, G. S., Sedoc, J., & Callison-Burch, C. (2019). Anonymization of sensitive information in medical health records. IberLEF@SEPLN, 2421, 647–653. http://ceur-ws.org/Vol-2421/MEDDOCAN_p aper_2.pdf Ulven, J. B., & Wangen, G. (2021). A systematic review of cybersecurity risks in higher education. Future Internet, 13(2), 39. https://doi.org/10.3390/fi13020039

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