Risk taxonomy, mitigation, and assessment benchmarks of large language model systems

T Cui, Y Wang, C Fu, Y Xiao, S Li, X Deng, Y Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) have strong capabilities in solving diverse natural language
processing tasks. However, the safety and security issues of LLM systems have become the …

N-sanitization: A semantic privacy-preserving framework for unstructured medical datasets

C Iwendi, SA Moqurrab, A Anjum, S Khan… - Computer …, 2020 - Elsevier
The introduction and rapid growth of the Internet of Medical Things (IoMT), a subset of the
Internet of Things (IoT) in the medical and healthcare systems, has brought numerous …

Man vs the machine in the struggle for effective text anonymisation in the age of large language models

C Patsakis, N Lykousas - Scientific Reports, 2023 - nature.com
The collection and use of personal data are becoming more common in today's data-driven
culture. While there are many advantages to this, including better decision-making and …

A deep learning model for information loss prevention from multi-page digital documents

A Guha, D Samanta, A Banerjee, D Agarwal - IEEE Access, 2021 - ieeexplore.ieee.org
World Wide Web has redefined almost all the business models in the past twenty-five to
thirty years. IoT, Big Data, AI are some of the comparatively recent technologies which …

Connecting pixels to privacy and utility: Automatic redaction of private information in images

T Orekondy, M Fritz, B Schiele - Proceedings of the IEEE …, 2018 - openaccess.thecvf.com
Images convey a broad spectrum of personal information. If such images are shared on
social media platforms, this personal information is leaked which conflicts with the privacy of …

C‐sanitized: A privacy model for document redaction and sanitization

D Sánchez, M Batet - Journal of the Association for Information …, 2016 - Wiley Online Library
Vast amounts of information are daily exchanged and/or released. The sensitive nature of
much of this information creates a serious privacy threat when documents are uncontrollably …

Analysis and classification of privacy-sensitive content in social media posts

L Bioglio, RG Pensa - EPJ Data Science, 2022 - epjds.epj.org
User-generated contents often contain private information, even when they are shared
publicly on social media and on the web in general. Although many filtering and natural …

Content disarm and reconstruction of RTF files a zero file trust methodology

R Dubin - IEEE Transactions on Information Forensics and …, 2023 - ieeexplore.ieee.org
Content Disarm and Reconstruction (CDR) is a zero-trust file methodology that proactively
extracts threat attack vectors from documents and media files. While there is extensive …

Deep-Confidentiality: An IoT-Enabled Privacy-Preserving Framework for Unstructured Big Biomedical Data

SA Moqurrab, A Anjum, A Khan, M Ahmed… - ACM Transactions on …, 2021 - dl.acm.org
Due to the Internet of Things evolution, the clinical data is exponentially growing and using
smart technologies. The generated big biomedical data is confidential, as it contains a …

Content disarm and reconstruction of PDF files

R Dubin - Ieee Access, 2023 - ieeexplore.ieee.org
Content Disarm and Reconstruction (CDR) is a zero-trust file methodology that proactively
extracts threat attack vectors from documents and media files. While extensive literature on …