Results 61 to 70 of about 111,433 (205)

LLM‐Powered Data Synthesis on Blockchain for Fusion Isomerism Learning in Heterogeneous Federated Systems

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Severe data starvation, architectural heterogeneity and Byzantine vulnerabilities fundamentally impede the deployment of robust multiclass classification models in decentralised edge environments. To address these intertwined challenges, we propose fusion isomerism learning (FusionIL), a secure and domain‐agnostic framework that ...
Zhihao Hao, Longbing Cao, Han Yu, Xiaoqiang Teng, Guancheng Wang, Chuanbin Zhang   +5 more
wiley   +1 more source

Fully Homomorphic Encryption for Mathematicians [PDF]

, 2013
We give an introduction to Fully Homomorphic Encryption for mathematicians. Fully Homomorphic Encryption allows untrusted parties to take encrypted data Enc(m_1),...,Enc(m_t) and any efficiently computable function f, and compute an encryption of f(m_1,..
Alice Silverberg
core   +2 more sources

Experimental Demonstration of Quantum Fully Homomorphic Encryption with Application in a Two-Party Secure Protocol

Physical Review X, 2020
A fully homomorphic encryption system hides data from unauthorized parties while still allowing them to perform computations on the encrypted data. Aside from the straightforward benefit of allowing users to delegate computations to a more powerful ...
W. K. Tham, Hugo Ferretti, Kent Bonsma-Fisher, Aharon Brodutch, Barry C. Sanders, Aephraim M. Steinberg, Stacey Jeffery   +6 more
doaj   +1 more source

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

Software: Practice and Experience, Volume 56, Issue 12, Page 1538-1556, December 2026.
ABSTRACT Context The rapid increase in cyber threats, coupled with increasingly sophisticated attack strategies and the exponential growth of data in recent years, has exposed significant limitations in classical machine learning, rule‐based, and signature‐based defense mechanisms.
Siva Sai, Ishika Goyal, Shubham Sharma, Sri Harshita Manuri, Vinay Chamola, Rajkumar Buyya   +5 more
wiley   +1 more source

Introduction to Homomorphic Encryption and Schemes

, 2022
Homomorphic encryption (HE) enables processing encrypted data without decrypting it. This technology can be used, for example, to allow a public cloud to operate on secret data without the cloud learning anything about the data. Simply encrypt the secret
Polyakov, Yuriy, Yongsoo Song, Halevi, Shai, Jung Hee Cheon, Georgieva, Mariya, Gama, Nicolas, Wei Dai, Miran Kim, Yuriy Polyakov, Laine, Kim, Anamaria Costache, Nicolas Gama, Radames Cruz Moreno, Cheon, Jung Hee, Dai, Wei, Sunwoong Kim, Kim, Miran, Moreno, Radames Cruz, Song, Yongsoo, Kim, Sunwoong, Mariya Georgieva, Shai Halevi, Kim Laine, Costache, Anamaria   +23 more
core   +1 more source

Multi-identity Fully Homomorphic Encryption Scheme Supporting Threshold Decryption

工程科学与技术, 2019
In order to solve the problem that traditional identity-based fully homomorphic encryption schemes can only perform homomorphic operations and access control on ciphertexts under the same identity, a multi-identity fully homomorphic encryption scheme was
Xiaoyuan YANG, Guangsheng TU, Yongjun KONG, Tanping ZHOU   +3 more
doaj  

A Comprehensive Review on Federated and Incremental Learning in Spatial Crowdsourcing Systems

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 4, December 2026.
A comprehensive overview of Federated and Incremental Learning (FIL) integration in Spatial Crowdsourcing, highlighting privacy, security, adaptability, efficiency challenges, and future research directions. ABSTRACT Spatial Crowdsourcing (SC) coordinates workers and requesters through personal mobile devices to complete location‐dependent tasks in ...
Md Mujibur Rahman, Quazi Mamun, Michael Bewong, Md Zahidul Islam   +3 more
wiley   +1 more source

Federated Learning for Official Statistics: A Systematic Review of Privacy‐Preserving Architectures and the Path Toward GSBPM Integration

Concurrency and Computation: Practice and Experience, Volume 38, Issue 21, November 2026.
ABSTRACT National Statistical Offices (NSOs) face an escalating “privacy‐utility” impasse, where the demand for high‐granularity data must compete with the near zero risk tolerance of legal frameworks like the General Data Protection Regulation (GDPR).
Hooreya Khunji, Wael Elmedany, Nabil Hewahi, Mhd Saeed Sharif   +3 more
wiley   +1 more source

A quantum approach to homomorphic encryption [PDF]

Scientific Reports, 2016
AbstractEncryption schemes often derive their power from the properties of the underlying algebra on the symbols used. Inspired by group theoretic tools, we use the centralizer of a subgroup of operations to present a private-key quantum homomorphic encryption scheme that enables a broad class of quantum computation on encrypted data.
Tan, S.H., Kettlewell, J.A., Ouyang, Y., Chen, L., Fitzsimons, J.F.   +4 more
openaire   +4 more sources

Homomorphic encryption schemes [PDF]

, 2013
Title: Homomorphic encryption schemes Author: Anežka Titěrová Department: Department of Algebra Supervisor: RNDr. Alexandr Kazda, Department of Algebra Abstract: Rivest et al.
Titěrová, Anežka
core