Preserving privacy in large language models: A survey on current threats and solutions

M Miranda, ES Ruzzetti, A Santilli, FM Zanzotto… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) represent a significant advancement in artificial
intelligence, finding applications across various domains. However, their reliance on …

Private web search with Tiptoe

A Henzinger, E Dauterman, H Corrigan-Gibbs… - Proceedings of the 29th …, 2023 - dl.acm.org
Tiptoe is a private web search engine that allows clients to search over hundreds of millions
of documents, while revealing no information about their search query to the search engine's …

Privacy-and utility-preserving textual analysis via calibrated multivariate perturbations

O Feyisetan, B Balle, T Drake, T Diethe - … on web search and data mining, 2020 - dl.acm.org
Accurately learning from user data while providing quantifiable privacy guarantees provides
an opportunity to build better ML models while maintaining user trust. This paper presents a …

A basic framework for privacy protection in personalized information retrieval: An effective framework for user privacy protection

Z Wu, S Shen, H Li, H Zhou, C Lu - Journal of Organizational and …, 2021 - igi-global.com
Personalized information retrieval is an effective tool to solve the problem of information
overload. Along with the rapid development of emerging network technologies such as …

A confusion method for the protection of user topic privacy in Chinese keyword-based book retrieval

Z Wu, J **e, S Shen, C Lin, G Xu, E Chen - ACM transactions on asian …, 2023 - dl.acm.org
In this article, aiming at a Chinese keyword-based book search service, from a technological
perspective, we propose to modify a user query sequence carefully to confuse the user …

The protection of user preference privacy in personalized information retrieval: challenges and overviews

Z Wu, C Lu, Y Zhao, J **e, D Zou, X Su - Libri, 2021 - degruyter.com
This paper reviews a large number of research achievements relevant to user privacy
protection in an untrusted network environment, and then analyzes and evaluates their …

Suggesting points-of-interest via content-based, collaborative, and hybrid fusion methods in mobile devices

A Arampatzis, G Kalamatianos - ACM Transactions on Information …, 2017 - dl.acm.org
Recommending venues or points-of-interest (POIs) is a hot topic in recent years, especially
for tourism applications and mobile users. We propose and evaluate several suggestion …

QuPiD Attack: Machine Learning‐Based Privacy Quantification Mechanism for PIR Protocols in Health‐Related Web Search

R Khan, A Ahmad, AO Alsayed… - Scientific …, 2020 - Wiley Online Library
With the advancement in ICT, web search engines have become a preferred source to find
health‐related information published over the Internet. Google alone receives more than …

Query Obfuscation for Information Retrieval Through Differential Privacy

G Faggioli, N Ferro - European Conference on Information Retrieval, 2024 - Springer
Protecting the privacy of a user querying an Information Retrieval (IR) system is of utmost
importance. The problem is exacerbated when the IR system is not cooperative in satisfying …

Intent-aware query obfuscation for privacy protection in personalized web search

WU Ahmad, KW Chang, H Wang - … ACM SIGIR conference on research & …, 2018 - dl.acm.org
Modern web search engines exploit users' search history to personalize search results, with
a goal of improving their service utility on a per-user basis. But it is this very dimension that …