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Security of federated learning for cloud‐edge intelligence collaborative computing

https://doi.org/10.1002/int.22992
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/int.22529openalex-snapshot
Hybrid sequence‐based Android malware detection using natural language processing
inferredcites →https://doi.org/10.1007/978-3-030-58951-6_24openalex-snapshot
Data Poisoning Attacks Against Federated Learning Systems
inferredcites →https://doi.org/10.1007/978-3-030-63076-8_2openalex-snapshot
Deep Leakage from Gradients
inferredcites →https://doi.org/10.1007/978-3-030-70604-3_8openalex-snapshot
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
inferredcites →https://doi.org/10.1007/s10462-021-10098-wopenalex-snapshot
Federated learning attack surface: taxonomy, cyber defences, challenges, and future directions
inferredcites →https://doi.org/10.1016/j.ins.2020.09.064openalex-snapshot
PPCL: Privacy-preserving collaborative learning for mitigating indirect information leakage
inferredcites →https://doi.org/10.1016/j.ins.2021.01.046openalex-snapshot
MHAT: An efficient model-heterogenous aggregation training scheme for federated learning
inferredcites →https://doi.org/10.1109/csf.2018.00027openalex-snapshot
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00033openalex-snapshot
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01607openalex-snapshot
See through Gradients: Image Batch Recovery via GradInversion
inferredcites →https://doi.org/10.1109/eurosp53844.2022.00049openalex-snapshot
Dynamic Backdoor Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/iccv48922.2021.00072openalex-snapshot
Exploiting Explanations for Model Inversion Attacks
inferredcites →https://doi.org/10.1109/infocom.2019.8737416openalex-snapshot
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning
inferredcites →https://doi.org/10.1109/jiot.2020.3023126openalex-snapshot
PoisonGAN: Generative Poisoning Attacks Against Federated Learning in Edge Computing Systems
inferredcites →https://doi.org/10.1109/jiot.2021.3086910openalex-snapshot
Resource Allocation in IoT Edge Computing via Concurrent Federated Reinforcement Learning
inferredcites →https://doi.org/10.1109/jproc.2019.2918437openalex-snapshot
Edge Computing Security: State of the Art and Challenges
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2019.00029openalex-snapshot
Exploiting Unintended Feature Leakage in Collaborative Learning
inferredcites →https://doi.org/10.1109/sp.2019.00065openalex-snapshot
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2019.2894411openalex-snapshot
Searchable Symmetric Encryption with Forward Search Privacy
inferredcites →https://doi.org/10.1109/tdsc.2020.2971598openalex-snapshot
NPMML: A Framework for Non-interactive Privacy-preserving Multi-party Machine Learning
inferredcites →https://doi.org/10.1109/tdsc.2020.3015886openalex-snapshot
Efficient and Secure Outsourcing of Differentially Private Data Publishing With Multiple Evaluators
inferredcites →https://doi.org/10.1109/tdsc.2022.3143566openalex-snapshot
Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy
inferredcites →https://doi.org/10.1109/tkde.2020.3009221openalex-snapshot
MAS-Encryption and its Applications in Privacy-Preserving Classifiers
inferredcites →https://doi.org/10.1109/tkde.2020.3015835openalex-snapshot
The Dynamic Privacy-Preserving Mechanisms for Online Dynamic Social Networks
inferredcites →https://doi.org/10.1109/tkde.2022.3174044openalex-snapshot
GATrust: A Multi-Aspect Graph Attention Network Model for Trust Assessment in OSNs
inferredcites →https://doi.org/10.1145/2810103.2813677openalex-snapshot
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
inferredcites →https://doi.org/10.1145/3243734.3243834openalex-snapshot
Property Inference Attacks on Fully Connected Neural Networks using Permutation Invariant Representations
inferredcites →https://doi.org/10.1145/3298981openalex-snapshot
Federated Machine Learning
inferredcites →https://doi.org/10.1145/3359789.3359824openalex-snapshot
Model inversion attacks against collaborative inference
inferredcites →https://doi.org/10.1145/3372297.3417238openalex-snapshot
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models
inferredcites →https://doi.org/10.1145/3394486.3403064openalex-snapshot
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks
inferredcites →https://doi.org/10.1145/3529836.3529845openalex-snapshot
A highly efficient, confidential, and continuous federated learning backdoor attack strategy
inferredcites →https://doi.org/10.14722/ndss.2019.23119openalex-snapshot
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
inferredcites →https://doi.org/10.14722/ndss.2021.24434openalex-snapshot
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
inferredcites →https://doi.org/10.14722/ndss.2021.24498openalex-snapshot
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning
inferredcites →https://doi.org/10.2478/popets-2019-0067openalex-snapshot
Monte Carlo and Reconstruction Membership Inference Attacks against Generative Models
inferredcites →https://doi.org/10.3390/s20216230openalex-snapshot
Federated Learning in Smart City Sensing: Challenges and Opportunities
inferredcites →https://doi.org/10.3390/su14052500openalex-snapshot
Federated Learning Approach to Protect Healthcare Data over Big Data Scenario
inferredcites →https://doi.org/10.3390/sym11070892openalex-snapshot
Selective Poisoning Attack on Deep Neural Networks †
inferredcites →https://doi.org/10.48550/arxiv.2003.14053openalex-snapshot
Inverting Gradients -- How easy is it to break privacy in federated learning?
inferredcites →https://doi.org/10.48550/arxiv.2004.00225openalex-snapshot
MetaPoison: Practical General-purpose Clean-label Data Poisoning
inferredcites →https://doi.org/10.48550/arxiv.2010.08138openalex-snapshot
Input-Aware Dynamic Backdoor Attack

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4871453openalex-extracted
Enhancing Critical Infrastructure Cybersecurity: Collaborative Dnn Synthesis in the Cloud Continuum
inferred← citeshttps://doi.org/10.1002/spe.3180openalex-snapshot
A federated learning attack method based on edge collaboration via cloud
inferred← citeshttps://doi.org/10.1007/978-3-031-48573-2_85openalex-snapshot
Enhancing Cloud-Based Machine Learning Models with Federated Learning Techniques
inferred← citeshttps://doi.org/10.1007/978-3-031-54531-3_4openalex-snapshot
FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification
inferred← citeshttps://doi.org/10.1007/978-981-99-9785-5_7openalex-snapshot
DFaP: Data Filtering and Purification Against Backdoor Attacks
inferred← citeshttps://doi.org/10.1007/s10115-025-02416-3openalex-snapshot
An intelligent secure and efficient workflow scheduling (SEWS) model for heterogeneous cloud computing environment
inferred← citeshttps://doi.org/10.1007/s41060-026-01173-yopenalex-snapshot
Federated and privacy-preserving learning in neurological imaging: a systematic review of frameworks, applications, and evidence gaps
inferred← citeshttps://doi.org/10.1016/j.comnet.2023.109947openalex-snapshot
A heterogeneous network structure publishing security framework based on cloud-edge collaboration
inferred← citeshttps://doi.org/10.1016/j.ins.2024.120713openalex-snapshot
Accelerating page loads via streamlining JavaScript engine for distributed learning
inferred← citeshttps://doi.org/10.1016/j.iot.2025.101558openalex-snapshot
Towards privacy-preserving split learning: Destabilizing adversarial inference and reconstruction attacks in the cloud
inferred← citeshttps://doi.org/10.1016/j.ipm.2022.103167openalex-snapshot
A privacy preserving framework for federated learning in smart healthcare systems
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.126897openalex-snapshot
A review of secure federated learning: Privacy leakage threats, protection technologies, challenges and future directions
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128166openalex-snapshot
A review of privacy-preserving research on federated graph neural networks
inferred← citeshttps://doi.org/10.1016/j.suscom.2026.101354openalex-snapshot
Reliable and privacy-preserving collaborative AI in multi-tier distributed architectures
inferred← citeshttps://doi.org/10.1080/03772063.2025.2590756openalex-snapshot
Blockchain-Enhanced Homomorphic Encryption for Neuro-Signal Driven Collaborative Intelligence in Secure Adaptive Learning Environments
inferred← citeshttps://doi.org/10.1109/acait63902.2024.11022155openalex-snapshot
Merkel Tree Combines the "Cloud-Edge-to-End" Multi-Level Collaborative Security Architecture of Blockchain
inferred← citeshttps://doi.org/10.1109/access.2025.3595665openalex-snapshot
LLM-Driven APT Detection for 6G Wireless Networks: A Systematic Review and Taxonomy
inferred← citeshttps://doi.org/10.1109/asiancon66527.2025.11281070openalex-snapshot
Federated Learning Framework for Secure Data Sharing and Governance in Oracle Cloud Environments
inferred← citeshttps://doi.org/10.1109/bibe60311.2023.00031openalex-snapshot
Boosting Classification Tasks with Federated Learning: Concepts, Experiments and Perspectives
inferred← citeshttps://doi.org/10.1109/comst.2024.3361451openalex-snapshot
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1109/icbctis59921.2023.00035openalex-snapshot
IoV Edge Data Integrity Audit Method Based on Blockchain
inferred← citeshttps://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom59178.2023.00094openalex-snapshot
PE-FedAvg: A Privacy-Enhanced Federated Learning for Distributed Android Malware Detection
inferred← citeshttps://doi.org/10.1109/syscon53073.2023.10131082openalex-snapshot
Collaborative Edge-Cloud AI for IoT Driven Secure Healthcare System
inferred← citeshttps://doi.org/10.1109/tce.2023.3325138openalex-snapshot
A Federated Deep Learning Framework for Privacy-Preserving Consumer Electronics Recommendations
inferred← citeshttps://doi.org/10.1109/tsc.2025.3586152openalex-snapshot
Integrating IoT and 6G: Applications of Edge Intelligence, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.1145/3633637.3633676openalex-snapshot
Efficient Task Scheduling for Federated Learning-Driven Image Recognition in Cloud-Edge Collaborative Environments
inferred← citeshttps://doi.org/10.2139/ssrn.5062204openalex-snapshot
Towards Privacy-Preserving Split Learning: Destabilizing Adversarial Inference and Reconstruction Attacks in the Cloud
inferred← citeshttps://doi.org/10.3390/app13031911openalex-snapshot
Hybrid Classifier-Based Federated Learning in Health Service Providers for Cardiovascular Disease Prediction
inferred← citeshttps://doi.org/10.3390/electronics14132512openalex-snapshot
A Review on Federated Learning Architectures for Privacy-Preserving AI: Lightweight and Secure Cloud–Edge–End Collaboration
inferred← citeshttps://doi.org/10.4236/jis.2026.171001openalex-snapshot
Artificial Intelligence Systems Cybersecurity Ensuring: Analysis of Vulnerabilities, Attacks, and Countermeasures
inferred← citeshttps://doi.org/10.7717/peerj-cs.1298openalex-snapshot
Optimization design of railway logistics center layout based on mobile cloud edge computing
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