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Trusted AI in Multiagent Systems: An Overview of Privacy and Security for Distributed Learning
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Communication Security in Multi-agent Systems
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Practical Black-Box Attacks on Deep Neural Networks Using Efficient Query Mechanisms
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Explainable Multi-Agent Systems Through Blockchain Technology
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Collaborative Fairness in Federated Learning
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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/10.1007/978-3-030-86130-8_16openalex-snapshot
A Verifiable Federated Learning Scheme Based on Secure Multi-party Computation
inferredcites →https://doi.org/10.1007/978-3-031-01834-3openalex-snapshot
Privacy-Preserving Data Publishing
inferredcites →https://doi.org/10.1007/978-3-319-56614-6_8openalex-snapshot
High-Throughput Secure Three-Party Computation for Malicious Adversaries and an Honest Majority
inferredcites →https://doi.org/10.1007/978-3-319-62416-7_19openalex-snapshot
Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks
inferredcites →https://doi.org/10.1007/978-3-540-24676-3_1openalex-snapshot
Efficient Private Matching and Set Intersection
inferredcites →https://doi.org/10.1007/978-3-540-79228-4_1openalex-snapshot
Differential Privacy: A Survey of Results
inferredcites →https://doi.org/10.1007/978-3-642-37682-5_1openalex-snapshot
ML Confidential: Machine Learning on Encrypted Data
inferredcites →https://doi.org/10.1007/978-981-10-5421-1_9openalex-snapshot
Privacy-Preserving Deep Learning: Revisited and Enhanced
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Granny and the robots: ethical issues in robot care for the elderly
inferredcites →https://doi.org/10.1007/s13748-012-0035-5openalex-snapshot
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Principles of Transaction Processing
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A survey of machine learning-based solutions to protect privacy in the Internet of Things
inferredcites →https://doi.org/10.1016/j.eng.2016.02.008openalex-snapshot
Strategies and Principles of Distributed Machine Learning on Big Data
inferredcites →https://doi.org/10.1016/j.eswa.2020.113406openalex-snapshot
A comparative evaluation of aggregation methods for machine learning over vertically partitioned data
inferredcites →https://doi.org/10.1016/j.jbi.2014.04.003openalex-snapshot
Private predictive analysis on encrypted medical data
inferredcites →https://doi.org/10.1016/j.jnca.2018.05.003openalex-snapshot
Distributed learning of deep neural network over multiple agents
inferredcites →https://doi.org/10.1016/j.jocs.2015.09.008openalex-snapshot
Large-scale machine learning based on functional networks for biomedical big data with high performance computing platforms
inferredcites →https://doi.org/10.1016/j.neucom.2022.01.063openalex-snapshot
A unified framework for multi-modal federated learning
inferredcites →https://doi.org/10.1016/j.sysconle.2011.10.013openalex-snapshot
Iterative learning approaches to design finite-time consensus protocols for multi-agent systems
inferredcites →https://doi.org/10.1038/ncomms4074openalex-snapshot
Quantum computing on encrypted data
inferredcites →https://doi.org/10.1038/s41467-022-29763-xopenalex-snapshot
Communication-efficient federated learning via knowledge distillation
inferredcites →https://doi.org/10.1049/iet-cta.2011.0047openalex-snapshot
Finite-time consensus for multi-agent systems via terminal feedback iterative learning
inferredcites →https://doi.org/10.1049/iet-cta.2012.0048openalex-snapshot
Adaptive iterative learning control for consensus of multi‐agent systems
inferredcites →https://doi.org/10.1080/01621459.1965.10480775openalex-snapshot
Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
inferredcites →https://doi.org/10.1109/69.971193openalex-snapshot
Protecting respondents identities in microdata release
inferredcites →https://doi.org/10.1109/access.2020.2974712openalex-snapshot
Generalization of Convolutional Neural Networks for ECG Classification Using Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/allerton.2013.6736718openalex-snapshot
Local privacy and statistical minimax rates
inferredcites →https://doi.org/10.1109/allerton.2015.7447103openalex-snapshot
Privacy-preserving deep learning
inferredcites →https://doi.org/10.1109/ccgrid49817.2020.00-52openalex-snapshot
Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning
inferredcites →https://doi.org/10.1109/ccgrid51090.2021.00101openalex-snapshot
Partially Encrypted Multi-Party Computation for Federated Learning
inferredcites →https://doi.org/10.1109/ccnc.2019.8651847openalex-snapshot
Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications
inferredcites →https://doi.org/10.1109/compsac.2007.55openalex-snapshot
An Adaptive Security Model for Multi-agent Systems and Application to a Clinical Trials Environment
inferredcites →https://doi.org/10.1109/comst.2016.2633620openalex-snapshot
Graph Data Anonymization, De-Anonymization Attacks, and De-Anonymizability Quantification: A Survey
inferredcites →https://doi.org/10.1109/comst.2020.2986024openalex-snapshot
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/csf.2017.10openalex-snapshot
On the Protection of Private Information in Machine Learning Systems: Two Recent Approches
inferredcites →https://doi.org/10.1109/cvpr.2018.00175openalex-snapshot
Robust Physical-World Attacks on Deep Learning Visual Classification
inferredcites →https://doi.org/10.1109/cvpr.2018.00957openalex-snapshot
Boosting Adversarial Attacks with Momentum
inferredcites →https://doi.org/10.1109/cvpr.2019.00509openalex-snapshot
Knockoff Nets: Stealing Functionality of Black-Box Models
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00040openalex-snapshot
Benchmarking Adversarial Robustness on Image Classification
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00549openalex-snapshot
CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00502openalex-snapshot
Scalable Differential Privacy with Sparse Network Finetuning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00993openalex-snapshot
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning
inferredcites →https://doi.org/10.1109/dac18072.2020.9218663openalex-snapshot
TrojDRL: Evaluation of Backdoor Attacks on Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/dcc.2019.00101openalex-snapshot
An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning
inferredcites →https://doi.org/10.1109/dsn-w50199.2020.00013openalex-snapshot
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information
inferredcites →https://doi.org/10.1109/ficloud.2016.43openalex-snapshot
Mobile Multi-agent Systems for the Internet-of-Things and Clouds Using the JavaScript Agent Machine Platform and Machine Learning as a Service
inferredcites →https://doi.org/10.1109/focs.2015.46openalex-snapshot
Robust Traceability from Trace Amounts
inferredcites →https://doi.org/10.1109/iccv48922.2021.01480openalex-snapshot
Ensemble Attention Distillation for Privacy-Preserving Federated Learning
inferredcites →https://doi.org/10.1109/icdcs.2015.40openalex-snapshot
Privacy-Preserving Machine Learning Algorithms for Big Data Systems
inferredcites →https://doi.org/10.1109/icde.2007.367856openalex-snapshot
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
inferredcites →https://doi.org/10.1109/icde.2019.00133openalex-snapshot
Adaptive Dynamic Bipartite Graph Matching: A Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/icde48307.2020.00050openalex-snapshot
Providing Input-Discriminative Protection for Local Differential Privacy
inferredcites →https://doi.org/10.1109/icde51399.2021.00023openalex-snapshot
Feature Inference Attack on Model Predictions in Vertical Federated Learning
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/infocom41043.2020.9155268openalex-snapshot
An Incentive Mechanism Design for Efficient Edge Learning by Deep Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/infocom48880.2022.9796724openalex-snapshot
Towards Optimal Multi-Modal Federated Learning on Non-IID Data with Hierarchical Gradient Blending
inferredcites →https://doi.org/10.1109/is.2018.8710454openalex-snapshot
Towards Blockchain-Based Robonomics: Autonomous Agents Behavior Validation
inferredcites →https://doi.org/10.1109/iscturkey53027.2021.9654360openalex-snapshot
Digital Twin Security Threats and Countermeasures: An Introduction
inferredcites →https://doi.org/10.1109/jiot.2017.2694844openalex-snapshot
A Survey on Security and Privacy Issues in Internet-of-Things
inferredcites →https://doi.org/10.1109/jiot.2021.3072611openalex-snapshot
Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
inferredcites →https://doi.org/10.1109/jiot.2021.3079472openalex-snapshot
Federated Learning With Unreliable Clients: Performance Analysis and Mechanism Design
inferredcites →https://doi.org/10.1109/jproc.2019.2921977openalex-snapshot
Deep Learning With Edge Computing: A Review
inferredcites →https://doi.org/10.1109/jproc.2020.2976475openalex-snapshot
Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/jsac.2022.3213344openalex-snapshot
Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing
inferredcites →https://doi.org/10.1109/jsac.2022.3213345openalex-snapshot
A Fast Blockchain-Based Federated Learning Framework With Compressed Communications
inferredcites →https://doi.org/10.1109/mci.2020.2976185openalex-snapshot
A Survey on Differentially Private Machine Learning [Review Article]
inferredcites →https://doi.org/10.1109/mci.2022.3180932openalex-snapshot
When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm
inferredcites →https://doi.org/10.1109/mcom.001.1900091openalex-snapshot
Data Security Issues in Deep Learning: Attacks, Countermeasures, and Opportunities
inferredcites →https://doi.org/10.1109/mcom.001.1900107openalex-snapshot
Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network
inferredcites →https://doi.org/10.1109/mnet.001.1900506openalex-snapshot
On Safeguarding Privacy and Security in the Framework of Federated Learning
inferredcites →https://doi.org/10.1109/mnet.011.2000783openalex-snapshot
Coordinated Backdoor Attacks against Federated Learning with Model-Dependent Triggers
inferredcites →https://doi.org/10.1109/msp.2018.3761710openalex-snapshot
Quantum Computing: Codebreaking and Beyond
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/ojcs.2022.3188249openalex-snapshot
Fusing Blockchain and AI With Metaverse: A Survey
inferredcites →https://doi.org/10.1109/ojcs.2022.3217565openalex-snapshot
When Digital Economy Meets Web3.0: Applications and Challenges
inferredcites →https://doi.org/10.1109/ro-man50785.2021.9515399openalex-snapshot
Do you remember me? Ethical Issues in Long-term Social Robot Interactions
inferredcites →https://doi.org/10.1109/soca.2014.58openalex-snapshot
IoT Security: Ongoing Challenges and Research Opportunities
inferredcites →https://doi.org/10.1109/sp.1985.10011openalex-snapshot
Cryptographic Protocol for Trustable Match Making
inferredcites →https://doi.org/10.1109/sp.1986.10022openalex-snapshot
A More Efficient Cryptographic Matchmaking Protocol for Use in the Absence of a Continuously Available Third Party
inferredcites →https://doi.org/10.1109/sp.2008.33openalex-snapshot
Robust De-anonymization of Large Sparse Datasets
inferredcites →https://doi.org/10.1109/sp.2011.40openalex-snapshot
"You Might Also Like:" Privacy Risks of Collaborative Filtering
inferredcites →https://doi.org/10.1109/sp.2013.30openalex-snapshot
Privacy-Preserving Ridge Regression on Hundreds of Millions of Records
inferredcites →https://doi.org/10.1109/sp.2017.12openalex-snapshot
SecureML: A System for Scalable Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1109/sp.2017.20openalex-snapshot
An Experimental Security Analysis of an Industrial Robot Controller
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2018.00038openalex-snapshot
Stealing Hyperparameters in Machine Learning
inferredcites →https://doi.org/10.1109/sp.2018.00057openalex-snapshot
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
inferredcites →https://doi.org/10.1109/sp.2019.00019openalex-snapshot
Differentially Private Model Publishing for Deep Learning
inferredcites →https://doi.org/10.1109/sp.2019.00029openalex-snapshot
Exploiting Unintended Feature Leakage in Collaborative Learning
inferredcites →https://doi.org/10.1109/sp40001.2021.00057openalex-snapshot
SGUARD: Towards Fixing Vulnerable Smart Contracts Automatically
inferredcites →https://doi.org/10.1109/sp40001.2021.00069openalex-snapshot
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning
inferredcites →https://doi.org/10.1109/sp46215.2023.10179336openalex-snapshot
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information
inferredcites →https://doi.org/10.1109/sp46215.2023.10179422openalex-snapshot
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy
inferredcites →https://doi.org/10.1109/syscon.2017.7934755openalex-snapshot
Secure communication for the robot operating system
inferredcites →https://doi.org/10.1109/tbdata.2022.3208736openalex-snapshot
Augmented Multi-Party Computation Against Gradient Leakage in Federated Learning
inferredcites →https://doi.org/10.1109/tc.2015.2470255openalex-snapshot
Privacy Preserving Deep Computation Model on Cloud for Big Data Feature Learning
inferredcites →https://doi.org/10.1109/tcyb.2019.2906574openalex-snapshot
Differentially Private Malicious Agent Avoidance in Multiagent Advising Learning
inferredcites →https://doi.org/10.1109/tdsc.2018.2881452openalex-snapshot
Privacy-Preserving Tensor Decomposition Over Encrypted Data in a Federated Cloud Environment
inferredcites →https://doi.org/10.1109/tdsc.2020.2986205openalex-snapshot
Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection
inferredcites →https://doi.org/10.1109/tdsc.2022.3208630openalex-snapshot
Your Labels are Selling You Out: Relation Leaks in Vertical Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2023.3274119openalex-snapshot
Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization
inferredcites →https://doi.org/10.1109/tdsc.2023.3276365openalex-snapshot
${\sf FederBoost}$: Private Federated Learning for GBDT
inferredcites →https://doi.org/10.1109/tdsc.2024.3521451openalex-snapshot
Feature Reconstruction Attacks and Countermeasures of DNN Training in Vertical Federated Learning
inferredcites →https://doi.org/10.1109/tifs.2017.2787987openalex-snapshot
Privacy-Preserving Deep Learning via Additively Homomorphic Encryption
inferredcites →https://doi.org/10.1109/tifs.2019.2925452openalex-snapshot
Selective Audio Adversarial Example in Evasion Attack on Speech Recognition System
inferredcites →https://doi.org/10.1109/tifs.2019.2929409openalex-snapshot
VerifyNet: Secure and Verifiable Federated Learning
inferredcites →https://doi.org/10.1109/tifs.2019.2931068openalex-snapshot
DP-ADMM: ADMM-Based Distributed Learning With Differential Privacy
inferredcites →https://doi.org/10.1109/tifs.2019.2946476openalex-snapshot
Privacy-Preserving Object Detection for Medical Images With Faster R-CNN
inferredcites →https://doi.org/10.1109/tifs.2020.2988132openalex-snapshot
PrivEdge: From Local to Distributed Private Training and Prediction
inferredcites →https://doi.org/10.1109/tifs.2020.2988575openalex-snapshot
Federated Learning With Differential Privacy: Algorithms and Performance Analysis
inferredcites →https://doi.org/10.1109/tifs.2020.3016835openalex-snapshot
Arbitrarily Strong Utility-Privacy Tradeoff in Multi-Agent Systems
inferredcites →https://doi.org/10.1109/tifs.2022.3212174openalex-snapshot
FLCert: Provably Secure Federated Learning Against Poisoning Attacks
inferredcites →https://doi.org/10.1109/tifs.2024.3356821openalex-snapshot
Similarity-Based Label Inference Attack Against Training and Inference of Split Learning
inferredcites →https://doi.org/10.1109/tii.2020.3010798openalex-snapshot
Communication-Efficient Federated Learning for Digital Twin Edge Networks in Industrial IoT
inferredcites →https://doi.org/10.1109/tit.2022.3161620openalex-snapshot
vqSGD: Vector Quantized Stochastic Gradient Descent
inferredcites →https://doi.org/10.1109/tkde.2011.78openalex-snapshot
Improving Security and Efficiency in Attribute-Based Data Sharing
inferredcites →https://doi.org/10.1109/tkde.2018.2841360openalex-snapshot
A Utility-Optimized Framework for Personalized Private Histogram Estimation
inferredcites →https://doi.org/10.1109/tkde.2020.2964658openalex-snapshot
Privacy Preserving Location Data Publishing: A Machine Learning Approach
inferredcites →https://doi.org/10.1109/tkde.2020.3014246openalex-snapshot
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence
inferredcites →https://doi.org/10.1109/tkde.2023.3241442openalex-snapshot
A Distributed Privacy-Preserving Learning Dynamics in General Social Networks
inferredcites →https://doi.org/10.1109/tmc.2020.2993599openalex-snapshot
Privacy Preservation in Location-Based Services: A Novel Metric and Attack Model
inferredcites →https://doi.org/10.1109/tmc.2021.3070013openalex-snapshot
Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training With Non-IID Private Data
inferredcites →https://doi.org/10.1109/tnnls.2018.2886017openalex-snapshot
Adversarial Examples: Attacks and Defenses for Deep Learning
inferredcites →https://doi.org/10.1109/tnnls.2022.3166101openalex-snapshot
Model Pruning Enables Efficient Federated Learning on Edge Devices
inferredcites →https://doi.org/10.1109/tpds.2013.18openalex-snapshot
Privacy Preserving Back-Propagation Neural Network Learning Made Practical with Cloud Computing
inferredcites →https://doi.org/10.1109/tpds.2021.3138848openalex-snapshot
Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation
inferredcites →https://doi.org/10.1109/tsmcc.2010.2084571openalex-snapshot
A Multifaceted Approach to Modeling Agent Trust for Effective Communication in the Application of Mobile Ad Hoc Vehicular Networks
inferredcites →https://doi.org/10.1109/tsp.2020.3033483openalex-snapshot
Optimal Local Differentially Private Quantization
inferredcites →https://doi.org/10.1109/tsp.2022.3153135openalex-snapshot
Robust Aggregation for Federated Learning
inferredcites →https://doi.org/10.1109/tvt.2022.3204839openalex-snapshot
Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach
inferredcites →https://doi.org/10.1109/twc.2019.2927312openalex-snapshot
Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn From a Digital Twin
inferredcites →https://doi.org/10.1109/twc.2022.3219501openalex-snapshot
Blockchain Assisted Federated Learning Over Wireless Channels: Dynamic Resource Allocation and Client Scheduling
inferredcites →https://doi.org/10.1109/wcnc45663.2020.9120770openalex-snapshot
Adversarial Jamming Attacks on Deep Reinforcement Learning Based Dynamic Multichannel Access
inferredcites →https://doi.org/10.1109/wimob.2017.8115788openalex-snapshot
Secure lightweight ECC-based protocol for multi-agent IoT systems
inferredcites →https://doi.org/10.1137/1.9781611972740.21openalex-snapshot
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification
inferredcites →https://doi.org/10.1142/s0218488502001648openalex-snapshot
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
inferredcites →https://doi.org/10.1145/1455770.1455832openalex-snapshot
Constructions of truly practical secure protocols using standardsmartcards
inferredcites →https://doi.org/10.1145/1529282.1529574openalex-snapshot
A personalized framework for trust assessment
inferredcites →https://doi.org/10.1145/1749603.1749605openalex-snapshot
Privacy-preserving data publishing
inferredcites →https://doi.org/10.1145/2508859.2516701openalex-snapshot
When private set intersection meets big data
inferredcites →https://doi.org/10.1145/2588555.2610509openalex-snapshot
Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation
inferredcites →https://doi.org/10.1145/2810103.2813677openalex-snapshot
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
inferredcites →https://doi.org/10.1145/2810103.2813705openalex-snapshot
Fast and Secure Three-party Computation
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/2976749.2978331openalex-snapshot
High-Throughput Semi-Honest Secure Three-Party Computation with an Honest Majority
inferredcites →https://doi.org/10.1145/2976749.2978355openalex-snapshot
Membership Privacy in MicroRNA-based Studies
inferredcites →https://doi.org/10.1145/3052973.3053009openalex-snapshot
Practical Black-Box Attacks against Machine Learning
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3133956.3134056openalex-snapshot
Oblivious Neural Network Predictions via MiniONN Transformations
inferredcites →https://doi.org/10.1145/3133956.3134077openalex-snapshot
Machine Learning Models that Remember Too Much
inferredcites →https://doi.org/10.1145/3214303openalex-snapshot
A Survey on Homomorphic Encryption Schemes
inferredcites →https://doi.org/10.1145/3302505.3310068openalex-snapshot
Mobile sensor data anonymization
inferredcites →https://doi.org/10.1145/3320269.3384740openalex-snapshot
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
inferredcites →https://doi.org/10.1145/3372297.3417238openalex-snapshot
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models
inferredcites →https://doi.org/10.1145/3377454openalex-snapshot
A Survey on Distributed Machine Learning
inferredcites →https://doi.org/10.1145/3385956.3418967openalex-snapshot
Anonymity vs. Familiarity: Self-Disclosure and Privacy in Social Virtual Reality
inferredcites →https://doi.org/10.1145/3387107openalex-snapshot
Federated learning for privacy-preserving AI
inferredcites →https://doi.org/10.1145/3394486.3403089openalex-snapshot
Malicious Attacks against Deep Reinforcement Learning Interpretations
inferredcites →https://doi.org/10.1145/3394486.3403125openalex-snapshot
TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations
inferredcites →https://doi.org/10.1145/3404835.3462989openalex-snapshot
FedCMR: Federated Cross-Modal Retrieval
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RobustFed: A Truth Inference Approach for Robust Federated Learning
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More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
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Machine Learning Classification over Encrypted Data
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Projected federated averaging with heterogeneous differential privacy
showing the first 200 of 266 · page through all 266
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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