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Fine-Tuning Large Language Models: Assessing Memorization and Redaction of Personally Identifiable Information [PDF]

Masteroppgave(MSc) in Master of Science in Business, Data Science for Business - Handelshøyskolen BI, 2024Memorization and redaction of Personally Identifiable Information (PII) in fine-tuned transformer-based Large Language Models (LLMs) is a new ...
Koren, Ulrik Wilhelm, Alfnes, Augusta Sverdrup   +1 more
core  

Diagnosing and Mitigating LLM Failures in Recognizing Culturally Specific Korean Names: An Error-Driven Prompting Framework

Applied Sciences
As large language models (LLMs) improve in understanding and reasoning, they are increasingly used in privacy protection tasks such as de-identification, privacy-sensitive text generation, and entity obfuscation.
Xiaonan Wang, Gyuri Choi, Subin An, Joeun Kang, Seoyoon Park, Hyeji Choi, Jongkyu Lee, Hansaem Kim   +7 more
doaj   +1 more source

Sign Up Wallet: A Blockchain based Personally Identifiable Information (PII) Masking using Lookup Substitution

2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)
Digital identity is akin to a digital version of a physical ID, such as a passport or driver’s license, containingvarious attributes that represent a user online. Currently, centralized and federated identity management systems,such as those enabling logins via Google or Facebook, dominate the digital landscape. While these systemssimplify access, they
P Kalyanasundaram, K Eniyaval, P Ravi, S Gowtham, N Dineshkumar   +4 more
openaire   +3 more sources

MetaSSI: A Framework for Personal Data Protection, Enhanced Cybersecurity and Privacy in Metaverse Virtual Reality Platforms

Future Internet
The Metaverse brings together components of parallel processing computing platforms, the digital development of physical systems, cutting-edge machine learning, and virtual identity to uncover a fully digitalized environment with equal properties to the ...
Faisal Fiaz, Syed Muhammad Sajjad, Zafar Iqbal, Muhammad Yousaf, Zia Muhammad   +4 more
doaj   +1 more source

De-Identification of Electronic Health Records Using Deep Learning and Transformers

Applied Sciences
Adoption of electronic health records (EHRs) has significantly advanced healthcare by enabling extensive data storage and analysis for clinical decisions and research.
Fatih Dilmaç, Adil Alpkocak
doaj   +1 more source

Meddies-PII: A Multilingual Framework for Personally Identifiable Information Extraction in Clinical De-identification

Clinical de-identification relies on accurately identifying personally identifiable information (PII). However, manually annotated datasets are costly to construct, while existing synthetic alternatives often provide limited details about their generation process or rely on relatively simple synthesis strategies.
Le, Linh Uyen, Tri, Ho Dinh, Hoang, Christian, Ha, Huy Hoang   +3 more
openaire   +2 more sources

Addressing Memorization and Aggregation Risks in AI: A Knowledge Graph Approach to Privacy

Applied Sciences
Recent studies have shown that AI models can memorize specific data records, resulting in sensitive data exposure through model access. Current privacy-enhancing technologies often overlook the crucial, context-dependent nature of privacy risk as they ...
Jinhui Zuo, Seok-Won Lee
doaj   +1 more source

B.8.5.2 - Confidentiality of Personally Identifiable Information About Library Users

, 2004
Old policy manual number 52.4.2Policy concerning confidentiality of personally identifiable information about library ...
Council
core  

Digital Privacy in Healthcare: State-of-the-Art and Future Vision

IEEE Access
The article draws inspiration from IEEE Digital Privacy, which explores attaining privacy goals for individuals in the digital realm. Privacy is an umbrella term that equates to respect for an individual’s dignity.
Shalaka S. Mahadik, Pranav M. Pawar, Raja Muthalagu, Neeli Rashmi Prasad, Sin-Kuen Hawkins, Dimitris Stripelis, Sreedhar Rao, Peter Ejim, Bruce Hecht   +8 more
doaj   +1 more source

When less data is better: Exploratory privacy-by-design in AI-based human resource analytics based on synthetic data

Journal of King Saud University: Computer and Information Sciences
The use of Artificial Intelligence (AI) in Human Resource (HR)-related processes raises ethical and legal concerns, within the European context governed by the GDPR. This study presents a proof-of-concept computational investigation proposing an approach
Cristina Iancu, Simona-Vasilica Oprea, Adela Bara, Denisa-Maria Iordache   +3 more
doaj   +1 more source