Information Leakage in Embedding Models

31 March 2020

Papers citing "Information Leakage in Embedding Models"

50 / 53 papers shown

Title
Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking Tianle Gu Zongqi Wang Kexin Huang Yuanqi Yao Xiangliang Zhang Yujiu Yang Xiuying Chen 12 0 0 20 May 2025
Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy Haoqi Wu Wei Dai Li Wang Qiang Yan SILM 40 0 0 09 May 2025
FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Zhihao Zeng Ziquan Fang Wei Shao Lu Chen Yunjun Gao FedML 57 0 0 08 May 2025
Prompt Inversion Attack against Collaborative Inference of Large Language Models Wenjie Qu Yuguang Zhou Yongji Wu Tingsong Xiao Binhang Yuan Heng Chang Jiaheng Zhang 79 0 0 12 Mar 2025
ALGEN: Few-shot Inversion Attacks on Textual Embeddings using Alignment and Generation Yiyi Chen Qiongkai Xu Johannes Bjerva 53 0 0 16 Feb 2025
Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study Eric Aubinais Philippe Formont Pablo Piantanida Elisabeth Gassiat 50 1 0 10 Feb 2025
Top Ten Challenges Towards Agentic Neural Graph Databases Jiaxin Bai Zehua Wang Yukun Zhou hang Yin Weizhi Fei ... Binhang Yuan Wei Wang Lei Chen Xiaofang Zhou Yangqiu Song 132 1 0 24 Jan 2025
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models Jiadong Lou Xu Yuan Rui Zhang Xingliang Yuan Neil Gong N. Tzeng AAML 45 1 0 19 Jan 2025
Navigating the Designs of Privacy-Preserving Fine-tuning for Large Language Models Haonan Shi Tu Ouyang An Wang 36 0 0 08 Jan 2025
On the Vulnerability of Text Sanitization Meng Tong Kejiang Chen Xiaojian Yuang Jing Liu Wenbo Zhang Nenghai Yu Jie Zhang 55 0 0 22 Oct 2024
Large Language Models are Easily Confused: A Quantitative Metric, Security Implications and Typological Analysis Yiyi Chen Qiongxiu Li Russa Biswas Johannes Bjerva 42 2 0 17 Oct 2024
A Different Level Text Protection Mechanism With Differential Privacy Qingwen Fu 41 0 0 05 Sep 2024
Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory Haoran Li Wei Fan Yulin Chen Jiayang Cheng Tianshu Chu Xuebing Zhou Peizhao Hu Yangqiu Song AILaw 58 3 0 19 Aug 2024
Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries Yu-Hsiang Huang Yuche Tsai Hsiang Hsiao Hong-Yi Lin Shou-De Lin SILM 46 8 0 12 Jun 2024
Reconstructing training data from document understanding models Jérémie Dentan Arnaud Paran A. Shabou AAML SyDa 54 1 0 05 Jun 2024
HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption Seewoo Lee Garam Lee Jung Woo Kim Junbum Shin Mun-Kyu Lee 38 26 0 21 Mar 2024
Membership Inference Attacks and Privacy in Topic Modeling Nico Manzonelli Wanrong Zhang Salil P. Vadhan 37 1 0 07 Mar 2024
OLViT: Multi-Modal State Tracking via Attention-Based Embeddings for Video-Grounded Dialog Adnen Abdessaied Manuel von Hochmeister Andreas Bulling 40 2 0 20 Feb 2024
Fundamental Limits of Membership Inference Attacks on Machine Learning Models Eric Aubinais Elisabeth Gassiat Pablo Piantanida MIACV 50 2 0 20 Oct 2023
Disentangling the Linguistic Competence of Privacy-Preserving BERT Stefan Arnold Nils Kemmerzell Annika Schreiner 35 0 0 17 Oct 2023
Text Embeddings Reveal (Almost) As Much As Text John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 30 96 0 10 Oct 2023
Ethicist: Targeted Training Data Extraction Through Loss Smoothed Soft Prompting and Calibrated Confidence Estimation Zhexin Zhang Jiaxin Wen Minlie Huang 38 32 0 10 Jul 2023
Protecting User Privacy in Remote Conversational Systems: A Privacy-Preserving framework based on text sanitization Zhigang Kan Linbo Qiao Hao Yu Liwen Peng Yifu Gao Dongsheng Li 30 20 0 14 Jun 2023
Training Data Extraction From Pre-trained Language Models: A Survey Shotaro Ishihara 37 46 0 25 May 2023
Privacy-Preserving Prompt Tuning for Large Language Model Services Yansong Li Zhixing Tan Yang Liu SILM VLM 55 64 0 10 May 2023
On the Adversarial Inversion of Deep Biometric Representations Gioacchino Tangari Shreesh Keskar Hassan Jameel Asghar Dali Kaafar AAML 39 2 0 12 Apr 2023
Multi-step Jailbreaking Privacy Attacks on ChatGPT Haoran Li Dadi Guo Wei Fan Mingshi Xu Jie Huang Fanpu Meng Yangqiu Song SILM 64 323 0 11 Apr 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 31 75 0 29 Dec 2022
When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods Zhuo Zhang Yuanhang Yang Yong Dai Lizhen Qu Zenglin Xu FedML 48 66 0 20 Dec 2022
Privacy-Preserving Text Classification on BERT Embeddings with Homomorphic Encryption Garam Lee Minsoo Kim J. Park Seung-won Hwang Jung Hee Cheon 38 17 0 05 Oct 2022
M^4I: Multi-modal Models Membership Inference Pingyi Hu Zihan Wang Ruoxi Sun Hu Wang Minhui Xue 39 26 0 15 Sep 2022
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots Waiman Si Michael Backes Jeremy Blackburn Emiliano De Cristofaro Gianluca Stringhini Savvas Zannettou Yang Zhang 36 58 0 07 Sep 2022
Data Provenance via Differential Auditing Xin Mu Ming Pang Feida Zhu 19 1 0 04 Sep 2022
Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models Xinlei He Zheng Li Weilin Xu Cory Cornelius Yang Zhang MIACV 38 24 0 22 Aug 2022
Differential Privacy in Natural Language Processing: The Story So Far Oleksandra Klymenko Stephen Meisenbacher Florian Matthes 34 15 0 17 Aug 2022
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset Peter Henderson M. Krass Lucia Zheng Neel Guha Christopher D. Manning Dan Jurafsky Daniel E. Ho AILaw ELM 135 97 0 01 Jul 2022
CryptoTL: Private, Efficient and Secure Transfer Learning Roman Walch Samuel Sousa Lukas Helminger Stefanie N. Lindstaedt Christian Rechberger A. Trugler 38 8 0 24 May 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 40 75 0 17 May 2022
You Are What You Write: Preserving Privacy in the Era of Large Language Models Richard Plant V. Giuffrida Dimitra Gkatzia PILM 38 19 0 20 Apr 2022
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks Fatemehsadat Mireshghallah Kartik Goyal Archit Uniyal Taylor Berg-Kirkpatrick Reza Shokri MIALM 32 152 0 08 Mar 2022
Deduplicating Training Data Mitigates Privacy Risks in Language Models Nikhil Kandpal Eric Wallace Colin Raffel PILM MU 54 275 0 14 Feb 2022
What Does it Mean for a Language Model to Preserve Privacy? Hannah Brown Katherine Lee Fatemehsadat Mireshghallah Reza Shokri Florian Tramèr PILM 58 232 0 11 Feb 2022
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 27 233 0 18 Nov 2021
Inference Attacks Against Graph Neural Networks Zhikun Zhang Min Chen Michael Backes Yun Shen Yang Zhang MIACV AAML GNN 33 50 0 06 Oct 2021
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning Hongbin Liu Jinyuan Jia Wenjie Qu Neil Zhenqiang Gong 6 94 0 25 Aug 2021
Membership Inference on Word Embedding and Beyond Saeed Mahloujifar Huseyin A. Inan Melissa Chase Esha Ghosh Marcello Hasegawa MIACV SILM 25 46 0 21 Jun 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 21 51 0 08 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 17 125 0 04 Feb 2021
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 33 109 0 07 Nov 2020