-
Fully Homomorphic Encryption (FHE) has the potential to substantially improve privacy and security by enabling computation directly on encrypted data. This is especially true with deep learning, as today, many popular user services are powered by neural networ…
datacite
Ebel, Austin, Garimella, Karthik, Reagen, Brandon
2023
置信度 0.66
Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
-
The convergence of fully homomorphic encryption (FHE) and machine learning offers unprecedented opportunities for private inference of sensitive data. FHE enables computation directly on encrypted data, safeguarding the entire machine learning pipeline, includ…
datacite
Roy, Arjun, Roy, Kaushik
2024
置信度 0.66
Cryptography and Security (cs.CR)Computer Vision and Pattern Recognition (cs.CV)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
-
Threshold fully homomorphic encryption (ThFHE) enables multiple parties to compute functions over their sensitive data without leaking data privacy. Most of existing ThFHE schemes are restricted to full threshold and require the participation of \textit{all} p…
datacite
Chang, Yijia, Li, Songze
2025
置信度 0.66
Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
-
The growing number of satellites in low Earth orbit (LEO) has increased concerns about the risk of satellite collisions, which can ultimately result in the irretrievable loss of satellites and a growing amount of space debris. To mitigate this risk, accurate c…
datacite
Lage, Svenja, Hörmann, Felicitas, Hanke, Felix, Karl, Michael
2025
置信度 0.66
Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
-
Fully homomorphic encryption (FHE) and zero-knowledge proofs (ZKPs) are emerging as solutions for data security in distributed environments. However, the widespread adoption of these encryption techniques is hindered by their significant computational overhead…
datacite
Zhang, Naifeng, Franchetti, Franz
2025
置信度 0.66
Programming Languages (cs.PL)Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
-
An exercise in implementing Scale Invariant Feature Transform using CKKS Fully Homomorphic encryption quickly reveals some glaring limitations in the current FHE paradigm. These limitations include the lack of a standard comparison operator and certain operati…
datacite
Balappanawar, Ishwar B, Kommireddy, Bhargav Srinivas
2024
置信度 0.66
Cryptography and Security (cs.CR)Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesI.4.m
-
Federated Learning (FL) aims to protect data privacy by enabling clients to collectively train machine learning models without sharing their raw data. However, recent studies demonstrate that information exchanged during FL is subject to Gradient Inversion Att…
datacite
Guo, Pengxin, Zeng, Shuang, Chen, Wenhao, Zhang, Xiaodan 等
2024
置信度 0.66
Machine Learning (cs.LG)Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
-
Fully Homomorphic Encryption (FHE) allows computations to be performed directly on encrypted data without needing to decrypt it first. This "encryption-in-use" feature is crucial for securely outsourcing computations in privacy-sensitive areas such as healthca…
datacite
Santriaji, Muhammad Husni, Xue, Jiaqi, Lou, Qian, Solihin, Yan
2024
置信度 0.66
Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
-
Two parties wish to collaborate on their datasets. However, before they reveal their datasets to each other, the parties want to have the guarantee that the collaboration would be fruitful. We look at this problem from the point of view of machine learning, wh…
datacite
Asghar, Hassan Jameel, Lu, Zhigang, Zhao, Zhongrui, Kaafar, Dali
2023
置信度 0.66
Cryptography and Security (cs.CR)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
-
crossref
Vinay Kumar Devara, Anshul Mishra, D. Ramesh
2026-02-20T21:13:18Z
置信度 0.70
-
crossref
Qingfeng Wang, Li-Ping Wang
2025-08-13T06:30:56Z
置信度 0.70
-
crossref
Minghui Zhang
2026-01-22T20:58:23Z
置信度 0.70
-
crossref
Abdullah Al Omar, Xin Yang, Euijin Choo, Omid Ardakanian
2026-03-06T20:57:57Z
置信度 0.70
-
Fully homomorphic encryption (FHE) enables operations to be performed directly on encrypted data without decryption. This preserves data privacy while leveraging the computational power of cloud computing. The security level of FHE is rooted in the hardness of…
crossref
Chien-Chih Huang, Hsuan-Jui Hsu, Qi-Xian Wu, Ming-Der Shieh
2025-09-10T13:36:19Z
置信度 0.70
-
crossref
Sei Nakanishi, Yoshiaki Narusue, Hiroyuki Morikawa
2025-09-17T17:29:26Z
置信度 0.70
-
crossref
Jinlong Pan, Yangyue Liu
2025-06-05T05:59:46Z
置信度 0.70
-
crossref
Sandeep M. Chitalkar, Prashant S. Dhotre
2025-03-27T02:18:17Z
置信度 0.70
-
crossref
Harald H. Paaske, Florian Bayer, Christian Rathgeb
2026-01-28T20:58:20Z
置信度 0.70
-
crossref
Chintala Mutyala Venkata Satya Murthy, Vrinda Gupta
2025-10-09T17:51:17Z
置信度 0.70
-
crossref
Zelei Jia, Zhexue Jin, Bin Huang
2025-05-27T17:05:15Z
置信度 0.70
-
crossref
Sangeen Khan, Huang Qiming
2025-03-17T05:40:48Z
置信度 0.70
-
crossref
Rojalini Tripathy, Jigyasa Meshram, Padmalochan Bera
2025-04-18T11:03:58Z
置信度 0.70
-
crossref
Lei Song, Leyi Shi, Xiuli Ren, Xiaoguang Li
2026-01-28T20:54:44Z
置信度 0.70
-
crossref
Preet Taparia, Shivam Sharma, Surbhi Chhabra
2026-05-01T19:51:31Z
置信度 0.70
-
crossref
Ramazan Akman, Gökhan Dalkılıç
2025-08-15T18:11:30Z
置信度 0.70
-
crossref
Bhawana S. Dakhare, Lata L. Ragha
2025-04-23T17:51:09Z
置信度 0.70
-
crossref
Tingxin Jiang N.A.
2024-09-10T13:03:17Z
置信度 0.70
-
crossref
Po-Chu Hsu, Ziying Yu, Shuhei Mise, Hideaki Miyaji
2025-03-27T02:16:58Z
置信度 0.70
-
crossref
Pragya Keshap, Arpana Hosabettu, Akshay Mittal
2026-03-17T20:18:48Z
置信度 0.70
-
crossref
Sajjad Akherati, Yok Jye Tang, Xinmiao Zhang
2025-06-27T17:42:19Z
置信度 0.70
-
crossref
Yu Li
2025-08-13T17:26:46Z
置信度 0.70
-
crossref
Aikata Aikata, Daniel Sanz Sobrino, Sujoy Sinha Roy
2025-05-21T17:36:35Z
置信度 0.70
-
crossref
Qiuxing Fu, Wei Li
2025-09-23T17:24:35Z
置信度 0.70
-
crossref
Sunita Godara, Simran Choudhary
2026-02-04T20:45:33Z
置信度 0.70
-
crossref
Gurdeep Singh, Sonam Mittal
2025-03-14T13:45:50Z
置信度 0.70
-
Homomorphic encryption (HE) schemes have gained significant popularity in modern privacy-preserving applications across various domains. While research on HE constructions based on learning with errors (LWE) and ring-LWE has received major attention from both …
crossref
Anisha Mukherjee, Sujoy Roy
2025-07-07T17:09:09Z
置信度 0.70
-
crossref
Wenhao Liu, Yingzi Hu, Wei Zhao, Lingling Wu 等
2025-07-14T12:36:54Z
置信度 0.70
-
crossref
Manuel Lengl, Simon Schumann, Stefan Röhrl, Oliver Hayden 等
2025-01-29T18:44:02Z
置信度 0.70
-
crossref
Nawal Almutairi
2025-09-23T01:35:36Z
置信度 0.70
-
The requirement for privacy-aware machine learning increases as we continue to use PII (personally identifiable information) within machine training. To overcome the existing privacy issues, we can apply fully homomorphic encryption (FHE) to encrypt data befor…
crossref
William J. Buchanan, Hisham Ali
2025-05-27T05:52:52Z
置信度 0.70
-
crossref
Doreen Dilip, V.K.Harini, R.M.Bhavadharini
2026-02-24T20:55:40Z
置信度 0.70
-
crossref
Ravindran K, S Nagendra Prabhu
2026-03-31T19:49:08Z
置信度 0.70
-
crossref
Kairong Liang, Huiyu Zhou, Peijia Zheng
2026-03-09T19:55:13Z
置信度 0.70
-
crossref
S. Gopalakrishnan, S. Sathiyanarayana, S. Santhosh, Shameem Ahamed. S. M
2025-10-17T17:38:30Z
置信度 0.70
-
crossref
Bian Zhu, Ling Niu
2025-01-18T00:38:27Z
置信度 0.70
-
crossref
Abiodun Okunola, asher asher
2025-05-29T19:10:07Z
置信度 0.70
-
crossref
Yixuan He, Yuta Kodera, Yasuyuki Nogami
2026-01-12T18:20:34Z
置信度 0.70
-
crossref
Ardianto Satriawan, Rella Mareta, Hanho Lee
2025-06-27T17:42:19Z
置信度 0.70
-
Homomorphic encryption revolutionizes financial analytics by enabling calculations on encrypted data without decryption, establishing a zero-trust framework where sensitive information is preserved in analytical processes. This cryptographic approach addresses…
crossref
Leela Krishna Yenigalla
2025-09-03T05:35:09Z
置信度 0.70
-
crossref
Hassan Rekabi Bana, Moslem Heidarpur, Mitra Mirhassani
2025-11-25T18:26:55Z
置信度 0.70
-
crossref
Rostin Shokri, Nektarios Georgios Tsoutsos
2025-07-07T17:47:34Z
置信度 0.70
-
crossref
Putrie Risky Khairunnisa, Muhamad Irsan, Ikke Dian Oktaviani
2025-09-15T17:36:17Z
置信度 0.70
-
crossref
Ketti Ramachandran Ramkumar, Sonam Mittal
2024-07-02T13:00:47Z
置信度 0.70
-
crossref
Tingxin Jiang
2025-10-28T12:30:27Z
置信度 0.70
-
crossref
Hoan Le
2026-04-09T19:42:34Z
置信度 0.70
-
crossref
Soufiane Ben Othman
2025-10-15T04:00:49Z
置信度 0.70
-
crossref
Xu Zhao, Zheng Yuan
2026-01-28T20:55:52Z
置信度 0.70
-
crossref
Zihao Chen∗
2025-08-24T01:23:34Z
置信度 0.70
-
crossref
Yacine Belhocine, Abdallah Meraoumia, Salim Chitroub, Hakim Bendjenna
2026-01-19T20:52:38Z
置信度 0.70
-
Federated Learning (FL) has occurred for example a privacy-preserving dispersed machine learning paradigm, allowing multiple participants to collaboratively train models without sharing raw information. However, FL remains susceptible to safety and privacy thr…
crossref
Sheela M S, Ankur Khare, Praveen Kumar K -
2025-10-13T09:24:02Z
置信度 0.70
-
crossref
Swetha P, M. Gautham Shetty, Pradeepta Panda, Srithesh Anchan 等
2025-10-28T22:00:17Z
置信度 0.70
-
crossref
Hua Cui
2025-08-30T13:00:44Z
置信度 0.70
-
Statistical confidentiality focuses on protecting data to preserve its analytical value while preventing identity exposure, ensuring privacy and security in any system handling sensitive information. Homomorphic encryption allows computations on encrypted data…
crossref
Yesem Kurt Peker, Rahul Raj
2025-12-26T02:07:58Z
置信度 0.70
-
crossref
Amin Tuni Gure, Mario A. Bochicchio
2026-03-06T20:57:57Z
置信度 0.70
-
crossref
Seoyoon Jang, Sungjin Park, Dongsuk Jeon
2025-03-04T14:32:21Z
置信度 0.70
-
crossref
Kalyan Cheerla, Lotfi Ben Othmane, Kirill Morozov
2025-11-13T18:42:42Z
置信度 0.70
-
crossref
S. Sathiya Devi, K. Jayasri
2025-05-09T17:56:12Z
置信度 0.70
-
crossref
Swayamveer Singh, Ayushmaan Ajay Amit, Ebru Celikel Cankaya
2025-12-04T18:35:03Z
置信度 0.70
-
crossref
Romio Rosan Sahani, Srinivasan Krishnaswamy, Gaurav Trivedi
2025-09-25T17:52:10Z
置信度 0.70
-
crossref
Seung-Chan Kim, Dong-Sun Kim
2025-02-18T18:17:22Z
置信度 0.70
-
Homomorphic Encryption enables biometric systems to perform matching directly on encrypted feature vectors, preserving user privacy throughout the process. However, the high computational cost of encrypted-domain operations, especially on high-dimensional inpu…
crossref
Andreis G. M. Purim
2025-09-11T13:10:33Z
置信度 0.70
-
crossref
Sophon Mongkolluksamee, Subhorn Khonthapagdee
2025-05-20T17:06:30Z
置信度 0.70
-
The development of cloud computing and big data has promoted the use of cloud servers in machine learning but has also raised concerns about privacy security. To enhance security and efficiency, this paper proposes a multi-key aggregation scheme based on impro…
crossref
Xiaoge Ma
2025-03-19T04:12:53Z
置信度 0.70
-
crossref
Junfeng Ye, Jie Ren
2025-10-13T09:40:43Z
置信度 0.70
-
crossref
Zhihan Xu, Rajgopal Kannan, Viktor K. Prasanna
2026-03-26T19:48:24Z
置信度 0.70
-
crossref
Xun Yi, Xuechao Yang, Xiaoning Liu, Andrei Kelarev 等
2025-07-15T14:47:18Z
置信度 0.70
-
crossref
Abderraouf Zaimen, Lubana Al Rayes, Nabil Hezil, Ahmed Bouridane 等
2025-07-02T17:42:13Z
置信度 0.70
-
crossref
Yuri Dimitre de Faria, Leandro A. Villas, Allan M. de Souza
2026-01-13T20:56:15Z
置信度 0.70
-
In the current era, there is increasing interest in data security, especially in cloud computing. Homomorphic Encryption (HE) supported by Artificial Intelligence (AI) technology offers a promising solution in this field. Homomorphic encryption ensures that co…
crossref
Qays Jabbar Abed
2025-03-26T07:31:01Z
置信度 0.70
-
This work presents a mathematical solution to data privacy and integrity issues in Split Learning which uses Homomorphic Encryption (HE) and Zero-Knowledge Proofs (ZKP). It allows calculations to be conducted on encrypted data, keeping the data private, while …
crossref
Agon Kokaj, Elissa Mollakuqe
2025-03-07T12:22:52Z
置信度 0.70
-
ABSTRACT Vehicular Ad Hoc Networks (VANETs) play a pivotal role in enabling intelligent transportation systems, yet their decentralized and dynamic nature exposes them to a wide range of cyber threats, including Sybil attacks, black hole attacks, replay, and m…
crossref
Haythem Hayouni
2025-09-30T10:25:13Z
置信度 0.70
-
crossref
Eren Ozilgili, Halil Ibrahim Kanpak, Alptekin Kupcu, Sinem Sav
2025-11-11T18:26:44Z
置信度 0.70
-
In the healthcare system, the application of predictive analysis is essential to the enhancement of patient benefits as well as the development of healthcare delivery systems. The digitization of health records presents an increasing threat of data leakage and…
crossref
Prokash Gogoi, Joseph Arul Valan
2025-11-05T09:37:04Z
置信度 0.70
-
crossref
Anguraju Krishnan, Rajesh Arunachalam
2025-12-01T18:23:00Z
置信度 0.70
-
The Internet of Vehicles (IoV) has emerged as a transformative technology, enabling seamless communication among vehicles and infrastructure to improve road safety, traffic efficiency, and passenger comfort. However, the pervasive collection and exchange of da…
crossref
Kyung-A Choi
2025-01-03T06:44:14Z
置信度 0.70
-
crossref
Diana-Elena Petrean, Rodica Potolea
2025-08-26T19:04:27Z
置信度 0.70
-
Electric vehicle (EV) charging infrastructures raise significant concerns about data security and user privacy because traditional centralized authorization and billing frameworks expose sensitive information to breaches and profiling. To address these vulnera…
crossref
Amjad Aldweesh, Someah Alangari
2025-08-18T13:28:22Z
置信度 0.70
-
In cloud-based not only SQL (NoSQL) databases, maintaining data privacy and the integrity are critically challenged by the risks of unauthorized external access and potential threats from malicious insiders. This paper presents a proxy-based solution that prov…
crossref
Abdelilah Belhaj, Soumia Ziti, Souad Najoua Lagmiri, Karim El Bouchti
2025-09-09T05:52:45Z
置信度 0.70
-
crossref
Shozo Saeki, Minoru Kawahara, Hirohisa Aman
2025-06-16T18:47:33Z
置信度 0.70
-
crossref
Sunil Gupta, Md Abu Sayeed
2025-12-19T18:56:43Z
置信度 0.70
-
crossref
Emilio Quaggiotto, Shiva Nejati, Alexander J. Leigh, Mitra Mirhassani
2025-04-22T17:37:30Z
置信度 0.70
-
crossref
Zefeng Ding, Haili Tang, Xiaojuan Cao
2025-09-21T13:00:21Z
置信度 0.70
-
crossref
Ke Zhang
2025-09-29T17:50:45Z
置信度 0.70
-
crossref
2025-02-25T19:56:21Z
置信度 0.70
-
crossref
Shahid Latif, Djamel Djenouri, Jawad Ahmad
2025-12-23T18:29:50Z
置信度 0.70
-
crossref
Avani Thakur
2025-12-26T14:40:50Z
置信度 0.70
-
crossref
Mohammed Shamar YADKAR, Sefer KURNAZ, Hameed Mutlag Farhan
2025-12-03T18:38:30Z
置信度 0.70
-
Abstract: Homomorphic encryption (HE) enables secure computations on encrypted data without decryption, offering a transformative solution for privacy-preserving computation. This review presents a ten-year retrospective (2014–2024) on HE’s evolution since Gen…
crossref
Aishwarya P. Deshmukh, Vivek Mahale, Ashok T. Gaikwad
2025-09-24T11:52:12Z
置信度 0.70
-
crossref
Yullivas Ameur, Idriss Taberkane, Samia Bouzefrane
2025-02-20T11:00:32Z
置信度 0.70
-
crossref
Zhenkun Yang, Suvadeep Banerjee, Jeremy Casas, Jin Yang
2025-05-30T17:43:30Z
置信度 0.70