• DHRUV RATHOD
• JEETESH MANE
• Dr Rakshitha Kiran P

As digital infor grows exponentially, the spread of digital infor increases exponentially. mation in various industries like healthcare, finance and gov- government, there is a danger of the accidental disclosure of privacy. information has gone up significantly. Personal Identifiable Information. mation (PII) - personal names, contact information, and so on. the identifiers issued by the government should be safely handled to provide enassured adherence to international privacy regulations including the Digital Personal Data Protection (DPDP) Act, the General. Data Protection Regulation (GDPR), and the Health Insurance. Portability and Accountability Act (HIPAA) [1], [2], [11], [15]. Traditional redaction is a manual process that is not efficient. uncapable, and unable to deal with large amounts of data, and prone. to the possible violation of sensitive content [10], [8]. To address this difficulty, this paper presents PiiCrunch a conceptual. system utilizing Machine Learning (ML) to do automation. identification and deidentification of PII in both written and scanned form. documents [17], [4]. The framework is a combination of Natural Language. Processing (NLP), Named Entity Recognition (NER) and Optical. OCR Character Recognition (OCR) to recognize and obscure sensitive data. data and maintains document readability and format. This document gives the general architecture of the system, processing. workflow, and expected performance and showing its potential. to improve the level of data confidentiality, reduce human work, and provide. secure document handling. Future upgrading will center on multilingual adaptability, deployment and model optimization. as a scalable cloud based solution.[7], [15].

PII Redaction, Data Privacy, Survey, Machine Learning, Named Entity Recognition, NLP, Data Security

"A Survey of Automated Techniques for Personal Identifiable Information (PII) Redaction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.d699-d704, November-2025, Available :http://www.jetir.org/papers/JETIR2511376.pdf

"A Survey of Automated Techniques for Personal Identifiable Information (PII) Redaction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppd699-d704, November-2025, Available at : http://www.jetir.org/papers/JETIR2511376.pdf