Results 81 to 90 of about 17,849,458 (195)

Analyzing Leakage of Personally Identifiable Information in Language Models

, 2023
Language Models (LMs) have been shown to leak information about training data through sentence-level membership inference and reconstruction attacks.
Tople, Shruti, Salem, Ahmed, Lukas, Nils, Sim, Robert, Zanella-Béguelin, Santiago, Wutschitz, Lukas   +5 more
core  

Identifying Unethical Personally Identifiable Information (PII) Privacy Violations Committed by IS/IT Practitioners: A Comparison to Computing Moral Exemplars [PDF]

, 2015
In some instances, Information Systems and Information Technology (IS/IT) practitioners have been noted to commit privacy violations to Personally Identifiable Information (PII).
Rosenbaum, Mark H.
core   +1 more source

Honey password vaults tolerating leakage of both personally identifiable information and passwords

Cybersecurity
Honey vaults are useful tools for password management. A vault usually contains usernames for each domain, and the corresponding passwords, encrypted with a master password chosen by the owner.
Chao An, YuTing Xiao, HaiHang Liu, Han Wu, Rui Zhang   +4 more
doaj   +1 more source

On the Applicability of LLMs and SLMs for Privacy-Preserving Named Entity Recognition in Financial Applications

Applied Sciences
This work explores how deep learning models, with different numbers of parameters, can be effectively applied to detect personal data within unstructured text using Named Entity Recognition (NER) techniques.
Evgenia Psarra, Kyriakos Stefanidis
doaj   +1 more source

Does fine-tuning GPT-3 with the OpenAI API leak personally-identifiable information? [PDF]

Machine learning practitioners often fine-tune generative pre-trained models like GPT-3 to improve model performance at specific tasks. Previous works, however, suggest that fine-tuned machine learning models memorize and emit sensitive information from ...
Mugunthan, Vaikkunth, Zemour, Eliott, Lau, Christian, Saxena, Arushi, Vaidyanathan, Udith, Sun, Albert Yu, Lin, Eric   +6 more
core   +1 more source

Corresponding Security Level with the Risk Factors of Personally Identifiable Information through the Analytic Hierarchy Process

, 2016
[[abstract]]Since Taiwan government has announced the New Version of Personal Information Protection Act , People began to pay attention to their personal information and privacy.
林詠章*;Lin, Y.W.;Lin, Y.W.;Wu, Y.S;Wu, Y.S
core  

Understanding how to identify and manage personal identifying information (PII) to further data interoperability

Journal of eScience Librarianship
Respect for research participant rights is a key aspect for consideration when creating and utilizing interoperable data. From that perspective, requirements for sharing research data often call for the data to be de-identified, i.e., the removal of all personal identifying information (PII) prior to data sharing, to ensure that the participant’s data ...
openaire   +2 more sources

European Trends in Privacy: How can we increase internet security and protect individual privacy? [PDF]

Journal of Systemics, Cybernetics and Informatics, 2004
In the aftermath of September 11 2001 security has been at the top of any Government or Enterprise agenda. Scrutinizing flight passenger lists, conference participants' background, customers' profile and securing access to public and private databases ...
Soren Duus Ostergaard
doaj  

SaaS API Monitoring for Data Leakage and Access Anomalies: A Privacy-Aware and Adaptive Behavioral Analytics Framework for Enterprise Cloud Systems

IEEE Access
Cloud-based Software as a Service (SaaS) generates large volumes of activity using dynamic, API-driven services, and traditional tools used for metadata scanning are unable to keep up with real-time visibility into that activity.
Sahana Markande, B. Nuthan, L. G. Abhinav, J. M. Chethohaar, Minal Moharir, P. Ramakanth Kumar, H. Pavithra, T. Praveena, Suresh Vishwanathan, Munal Suryakant Patel, Saravanan Gopalswamy   +10 more
doaj   +1 more source

PII-VisBench: Evaluating Personally Identifiable Information Safety in Vision Language Models Along a Continuum of Visibility

Findings of the Association for Computational Linguistics: ACL 2026
Vision Language Models (VLMs) are increasingly integrated into privacy-critical domains, yet existing evaluations of personally identifiable information (PII) leakage largely treat privacy as a static extraction task and ignore how a subject's online presence--the volume of their data available online--influences privacy alignment.
G. M. Shahariar, Zabir Al Nazi, Md. Olid Hasan Bhuiyan, Zhouxing Shi   +3 more
openaire   +3 more sources