Results 251 to 260 of about 1,042,683 (300)

PAPILLON: PrivAcy Preservation from Internet-based and Local Language MOdel ENsembles

North American Chapter of the Association for Computational Linguistics
Users can divulge sensitive information to proprietary LLM providers, raising significant privacy concerns. While open-source models, hosted locally on the user's machine, alleviate some concerns, models that users can host locally are often less capable
Siyan Li, Vethavikashini Chithrra Raghuram, Omar Khattab, Julia Hirschberg, Zhou Yu   +4 more
semanticscholar   +1 more source

Preserving Privacy at IXPs

Proceedings of the 2nd Asia-Pacific Workshop on Networking, 2018
Autonomous systems (ASes) on the Internet increasingly rely on Internet Exchange Points (IXPs) for peering. A single IXP may interconnect several 100s or 1000s of participants (ASes) all of which might peer with each other through BGP sessions. IXPs have addressed this scaling challenge through the use of route servers.
Xiaohe Hu, Arpit Gupta, Nick Feamster, Aurojit Panda, Scott Shenker   +4 more
openaire   +1 more source

Blockchain-Based Federated Learning Technique for Privacy Preservation and Security of Smart Electronic Health Records

IEEE transactions on consumer electronics
This study introduces a blockchain-based lightweight encryption strategy with federated learning to address the scalability and trust concerns of electronic health records (EHR).
M. Guduri, Chinmay Chakraborty, Uma Maheswari, Martin Margala   +3 more
semanticscholar   +1 more source

Efficiently Achieving Privacy Preservation and Poisoning Attack Resistance in Federated Learning

IEEE Transactions on Information Forensics and Security
Federated learning enables clients to train models locally and provide local updates to the server instead of raw dataset, thereby preserving data privacy to some extent.
Xueyang Li, Xue Yang, Zhengchun Zhou, Rongxing Lu   +3 more
semanticscholar   +1 more source

Security Compliant and Cooperative Pseudonyms Swapping for Location Privacy Preservation in VANETs

IEEE Transactions on Vehicular Technology, 2023
Vehicular Ad-hoc Networks (VANETs) are an essential part of the Intelligent Transportation System (ITS). VANETs promise to offer drivers and passengers safety, traffic efficiency, and infotainment services.
A. Mdee, Muhammad Toaha Raza Khan, Junho Seo, Dongkyun Kim   +3 more
semanticscholar   +1 more source

Deep Learning-Based Privacy Preservation and Data Analytics for IoT Enabled Healthcare

IEEE Transactions on Industrial Informatics, 2022
With the development of the industrial Internet of Things (IIoT), intelligent healthcare aims to build a platform to monitor users’ health-related information based on wearable devices remotely.
Hongliang Bi, Jiajia Liu, N. Kato
semanticscholar   +1 more source

Privacy-preserving deep learning

2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2015
Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text. The unprecedented accuracy of deep learning methods has turned them into the foundation of new AI-based services on the Internet.
Reza Shokri, Vitaly Shmatikov
openaire   +1 more source

Preserving security and privacy

IEEE Internet Computing, 2004
At the "Computers, Freedom, and Privacy (CFP) Conference held in Berkeley, California, the spotlight was on the twin weights of national security and personal liberty - with technology the fulcrum on which all turns. It highlights included sessions devoted to the new international cybercrime treaty, a global crusade to spread technology to ...
openaire   +1 more source

Efficient Federated Unlearning with Adaptive Differential Privacy Preservation

BigData Congress [Services Society]
Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients’ data on the global model in federated learning (FL), thereby granting individuals the "Right to be Forgotten".
Yu Jiang, Xindi Tong, Ziyao Liu, Huanyi Ye, C. Tan, Kwok-Yan Lam   +5 more
semanticscholar   +1 more source

HyDiscGAN: A Hybrid Distributed cGAN for Audio-Visual Privacy Preservation in Multimodal Sentiment Analysis

International Joint Conference on Artificial Intelligence
Multimodal Sentiment Analysis (MSA) aims to identify speakers' sentiment tendencies in multimodal video content, raising serious concerns about privacy risks associated with multimodal data, such as voiceprints and facial images.
Zhuojia Wu, Qi Zhang, Duoqian Miao, Kun Yi, Wei Fan, Liang Hu   +5 more
semanticscholar   +1 more source