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DeepSecure: Scalable Provably-Secure Deep Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-09699-5_3openalex-snapshot
Enhancing Privacy in Remote Data Classification
inferredcites →https://doi.org/10.1007/978-3-540-70583-3_40openalex-snapshot
Improved Garbled Circuit: Free XOR Gates and Applications
inferredcites →https://doi.org/10.1007/978-3-540-72540-4_4openalex-snapshot
An Efficient Protocol for Secure Two-Party Computation in the Presence of Malicious Adversaries
inferredcites →https://doi.org/10.1007/978-3-642-00457-5_22openalex-snapshot
LEGO for Two-Party Secure Computation
inferredcites →https://doi.org/10.1007/978-3-642-04101-3openalex-snapshot
Understanding Cryptography: A Textbook For Students And Practitioners
inferredcites →https://doi.org/10.1007/978-3-642-19571-6_20openalex-snapshot
Secure Two-Party Computation via Cut-and-Choose Oblivious Transfer
inferredcites →https://doi.org/10.1007/978-3-642-20465-4_22openalex-snapshot
Two-Output Secure Computation with Malicious Adversaries
inferredcites →https://doi.org/10.1007/s00145-004-0102-6openalex-snapshot
Computationally Secure Oblivious Transfer
inferredcites →https://doi.org/10.1038/505146aopenalex-snapshot
Computer science: The learning machines
inferredcites →https://doi.org/10.1049/ip-cds:19971587openalex-snapshot
Piecewise linear approximation applied to nonlinear function of a neural network
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/fccm.2017.43openalex-snapshot
Customizing Neural Networks for Efficient FPGA Implementation
inferredcites →https://doi.org/10.1109/iscas.2017.8050343openalex-snapshot
TinyDL: Just-in-time deep learning solution for constrained embedded systems
inferredcites →https://doi.org/10.1109/sfcs.1986.25openalex-snapshot
How to generate and exchange secrets
inferredcites →https://doi.org/10.1109/sp.2013.39openalex-snapshot
Efficient Garbling from a Fixed-Key Blockcipher
inferredcites →https://doi.org/10.1109/sp.2015.32openalex-snapshot
TinyGarble: Highly Compressed and Scalable Sequential Garbled Circuits
inferredcites →https://doi.org/10.1109/sp.2017.12openalex-snapshot
SecureML: A System for Scalable Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/1161366.1161393openalex-snapshot
A privacy-preserving protocol for neural-network-based computation
inferredcites →https://doi.org/10.1145/2382196.2382279openalex-snapshot
Foundations of garbled circuits
inferredcites →https://doi.org/10.1145/2810103.2813687openalex-snapshot
Privacy-Preserving Deep Learning
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3133956.3134056openalex-snapshot
Oblivious Neural Network Predictions via MiniONN Transformations
inferredcites →https://doi.org/10.1145/336992.337028openalex-snapshot
Privacy preserving auctions and mechanism design
inferredcites →https://doi.org/10.1155/2007/37343openalex-snapshot
Oblivious Neural Network Computing via Homomorphic Encryption
inferredcites →https://doi.org/10.1561/9781601988157openalex-snapshot
Deep Learning: Methods and Applications
inferredcites →https://doi.org/10.48550/arxiv.1503.08169openalex-snapshot
RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets
inferredcites →https://doi.org/10.48550/arxiv.1506.02626openalex-snapshot
Learning both Weights and Connections for Efficient Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1608.03665openalex-snapshot
Learning Structured Sparsity in Deep Neural Networks
inferredcites →https://doi.org/10.5555/2567709.2567741openalex-snapshot
Greedy feature selection for subspace clustering
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.4750344openalex-extracted
Blockchain-Based Distributed Federated Learning Using Proof of Accuracy Consensus
inferred← citeshttps://doi.org/10.1007/978-3-030-30619-9_4openalex-snapshot
A Survey on Deep Learning Techniques for Privacy-Preserving
inferred← citeshttps://doi.org/10.1007/978-3-030-86970-0_17openalex-snapshot
Secure Machine Intelligence and Distributed Ledger
inferred← citeshttps://doi.org/10.1007/978-3-031-32636-3_11openalex-snapshot
MOTUS: How Quantized Parameters Improve Protection of Model and Its Inference Input
inferred← citeshttps://doi.org/10.1007/978-3-031-40677-5_18openalex-snapshot
Adversarial ML for DNNs, CapsNets, and SNNs at the Edge
inferred← citeshttps://doi.org/10.1007/978-3-031-91524-6_9openalex-snapshot
Defense Methods for Adversarial Attacks and Privacy Issues in Secure AI
inferred← citeshttps://doi.org/10.1007/978-981-16-4486-3_3openalex-snapshot
A Systematic Review of Challenges and Techniques of Privacy-Preserving Machine Learning
inferred← citeshttps://doi.org/10.1007/978-981-96-4566-4_2openalex-snapshot
Efficient Two-Party Privacy-Preserving Ridge and Lasso Regression via SMPC
inferred← citeshttps://doi.org/10.1007/978-981-99-9803-6_1openalex-snapshot
Enhancing Security and Ownership Protection of Neural Networks Using Watermarking Techniques: A Systematic Literature Review Using PRISMA
inferred← citeshttps://doi.org/10.1007/s00521-024-10836-5openalex-snapshot
Enhanced facial action unit detection with adaptable patch sizes on representative landmarks
inferred← citeshttps://doi.org/10.1007/s10278-024-01384-4openalex-snapshot
A Faster Privacy-Preserving Medical Image Diagnosis Scheme with Machine Learning
inferred← citeshttps://doi.org/10.1007/s10462-024-11005-9openalex-snapshot
Robustness in deep learning models for medical diagnostics: security and adversarial challenges towards robust AI applications
inferred← citeshttps://doi.org/10.1007/s11227-025-07382-9openalex-snapshot
Low-cost ReLU search space compression, replacement, and recovery for efficient private network inference
inferred← citeshttps://doi.org/10.1016/j.cmpb.2025.108599openalex-snapshot
Towards practical and privacy-preserving CNN inference service for cloud-based medical imaging analysis: A homomorphic encryption-based approach
inferred← citeshttps://doi.org/10.1016/j.comnet.2022.108820openalex-snapshot
A survey: Distributed Machine Learning for 5G and beyond
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2021.107325openalex-snapshot
A novel privacy-preserving deep learning scheme without a cryptography component
inferred← citeshttps://doi.org/10.1016/j.future.2024.107560openalex-snapshot
Privacy-preserving and verifiable convolution neural network inference and training in cloud computing
inferred← citeshttps://doi.org/10.1016/j.ins.2021.05.054openalex-snapshot
SieveNet: Decoupling activation function neural network for privacy-preserving deep learning
inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104060openalex-snapshot
Vertin: Fast, Communication-friendly and Key-compact secure inference system for NNs and LLMs
inferred← citeshttps://doi.org/10.1016/j.jksuci.2024.102039openalex-snapshot
Privacy as a Lifestyle: Empowering assistive technologies for people with disabilities, challenges and future directions
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.111181openalex-snapshot
FPCNN: A fast privacy-preserving outsourced convolutional neural network with low-bandwidth
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.11.041openalex-snapshot
A review of privacy-preserving techniques for deep learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2022.01.061openalex-snapshot
Privacy-preserving and verifiable deep learning inference based on secret sharing
inferred← citeshttps://doi.org/10.1109/access.2019.2939410openalex-snapshot
MOBIUS: Model-Oblivious Binarized Neural Networks
inferred← citeshttps://doi.org/10.1109/access.2021.3111118openalex-snapshot
Challenges, Applications and Design Aspects of Federated Learning: A Survey
inferred← citeshttps://doi.org/10.1109/access.2022.3204037openalex-snapshot
A Survey and Guideline on Privacy Enhancing Technologies for Collaborative Machine Learning
inferred← citeshttps://doi.org/10.1109/access.2025.3528304openalex-snapshot
GuardianMPC: Backdoor-Resilient Neural Network Computation
inferred← citeshttps://doi.org/10.1109/acsac63791.2024.00045openalex-snapshot
Reading It like an Open Book: Single-trace Blind Side-channel Attacks on Garbled Circuit Frameworks
inferred← citeshttps://doi.org/10.1109/acsac67867.2025.00076openalex-snapshot
Mizar: Boosting Secure Three-Party Deep Learning with Co-Designed Sign-Bit Extraction and GPU Acceleration
inferred← citeshttps://doi.org/10.1109/ai4s56813.2022.00012openalex-snapshot
Practical Federated Learning Infrastructure for Privacy-Preserving Scientific Computing
inferred← citeshttps://doi.org/10.1109/aiccsa56895.2022.10017908openalex-snapshot
Early Detection of Diabetes Mellitus Using Differentially Private SGD in Federated Learning
inferred← citeshttps://doi.org/10.1109/asianhost.2018.8607161openalex-snapshot
Preventing Neural Network Model Exfiltration in Machine Learning Hardware Accelerators
inferred← citeshttps://doi.org/10.1109/asp-dac66049.2026.11420386openalex-snapshot
Silentflow: Leveraging Trusted Execution for Resource-Limited MPC via Hardware-Algorithm Co-design
inferred← citeshttps://doi.org/10.1109/asp-dac66049.2026.11420824openalex-snapshot
Safeguarding Neural Network IPs from Scan Chain based Model Extraction Attacks
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401707openalex-snapshot
CADHE: Privacy-Preserving Medical Image Analysis Through Homomorphic Encrypted Convolutional Networks
inferred← citeshttps://doi.org/10.1109/cloud55607.2022.00059openalex-snapshot
Towards Practical Privacy-Preserving Solution for Outsourced Neural Network Inference
inferred← citeshttps://doi.org/10.1109/cloud60044.2023.00071openalex-snapshot
Integrating Homomorphic Encryption and Trusted Execution Technology for Autonomous and Confidential Model Refining in Cloud
inferred← citeshttps://doi.org/10.1109/comsnets63942.2025.10885734openalex-snapshot
Secured and Privacy-Preserving GPU-Based Machine Learning Inference in Trusted Execution Environment: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1109/comst.2024.3430368openalex-snapshot
A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11581689openalex-snapshot
Enhancing Verifiable Federated Learning with Collusion-Resistant Verification
inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.00873openalex-snapshot
FALCON: A Fourier Transform Based Approach for Fast and Secure Convolutional Neural Network Predictions
inferred← citeshttps://doi.org/10.1109/cvprw53098.2021.00521openalex-snapshot
On the Application of Binary Neural Networks in Oblivious Inference
inferred← citeshttps://doi.org/10.1109/dac18074.2021.9586198openalex-snapshot
Privacy-Preserving Medical Image Segmentation via Hybrid Trusted Execution Environment
inferred← citeshttps://doi.org/10.1109/dac56929.2023.10247719openalex-snapshot
Primer: Fast Private Transformer Inference on Encrypted Data
inferred← citeshttps://doi.org/10.1109/dasc/picom/cbdcom/cyberscitech.2019.00035openalex-snapshot
Privacy-Preserving Deep Learning Models for Law Big Data Feature Learning
inferred← citeshttps://doi.org/10.1109/eurosp60621.2024.00031openalex-snapshot
Communication-Efficient Secure Logistic Regression
inferred← citeshttps://doi.org/10.1109/fdtc64268.2024.00015openalex-snapshot
FaultyGarble: Fault Attack on Secure Multiparty Neural Network Inference
inferred← citeshttps://doi.org/10.1109/hpca51647.2021.00013openalex-snapshot
Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11460321openalex-snapshot
Collusion-Resistant and Trusted Authority-Free Verifiable Federated Learning Via a Two-Server Architecture
inferred← citeshttps://doi.org/10.1109/icbats54253.2022.9759007openalex-snapshot
Privacy-Preserving Classification Method for Neural-Biomarkers using Homomorphic Residue Number System CNN: HoRNS-CNN
inferred← citeshttps://doi.org/10.1109/icc51166.2024.10622609openalex-snapshot
Roger: A Round Optimized GPU-Friendly Secure Inference Framework
inferred← citeshttps://doi.org/10.1109/iccad57390.2023.10323851openalex-snapshot
THE-V: Verifiable Privacy-Preserving Neural Network via Trusted Homomorphic Execution
inferred← citeshttps://doi.org/10.1109/icdcs60910.2024.00070openalex-snapshot
Accelerating and Securing Federated Learning with Stateless In-Network Aggregation at the Edge
inferred← citeshttps://doi.org/10.1109/icdis55630.2022.00027openalex-snapshot
PyHENet: A Generic Framework for Privacy-Preserving DL Inference Based on Fully Homomorphic Encryption
inferred← citeshttps://doi.org/10.1109/iceti63946.2024.10777155openalex-snapshot
Benchmarking TabLM: Evaluating the Performance of Language Models Against Traditional Machine Learning in Structured Data Tasks
inferred← citeshttps://doi.org/10.1109/icip.2018.8451239openalex-snapshot
Learning Sensitive Images Using Generative Models
inferred← citeshttps://doi.org/10.1109/icnwc57852.2023.10127281openalex-snapshot
Federated Learning with Internet of Things for Data Privacy and Security
inferred← citeshttps://doi.org/10.1109/icscc62041.2024.10690574openalex-snapshot
Secure Deep Learning Inference with Intel SGX on Intel Ice Lake-SP Xeon Processor
inferred← citeshttps://doi.org/10.1109/icws62655.2024.00061openalex-snapshot
Privacy-Preserving Artificial Intelligence on Edge Devices: A Homomorphic Encryption Approach
inferred← citeshttps://doi.org/10.1109/ijcb54206.2022.10007997openalex-snapshot
Inverting Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models
inferred← citeshttps://doi.org/10.1109/iscas66217.2026.11561937openalex-snapshot
Bridging Trust and Efficiency: TEE-Accelerated Nonlinear Evaluation in Multiparty Computing
inferred← citeshttps://doi.org/10.1109/isdfs69419.2026.11459073openalex-snapshot
Exploration of Bottlenecks and Optimizations in Privacy-Preserving Machine Learning Inference
inferred← citeshttps://doi.org/10.1109/jiot.2023.3338220openalex-snapshot
Privacy-Preserving Machine Learning Using Functional Encryption: Opportunities and Challenges
inferred← citeshttps://doi.org/10.1109/jiot.2024.3380597openalex-snapshot
Privacy-Preserving Serverless Federated Learning Scheme for Internet of Things
inferred← citeshttps://doi.org/10.1109/jiot.2025.3552321openalex-snapshot
BlindTuner: On Enhancement of Privacy-Preserving Fine-Tuning of Transformers Based on Homomorphic Encryption
inferred← citeshttps://doi.org/10.1109/jiot.2026.3718530openalex-snapshot
USD2C: UAV-Assisted Secure Data Collection and Computation Framework for Internet of Multimedia Things (IoMT) Applications
inferred← citeshttps://doi.org/10.1109/jstars.2023.3260867openalex-snapshot
A Generic Cryptographic Deep-Learning Inference Platform for Remote Sensing Scenes
inferred← citeshttps://doi.org/10.1109/mnet.127.2200342openalex-snapshot
Privacy-Preserving Machine Learning as a Service: Challenges and Opportunities
inferred← citeshttps://doi.org/10.1109/msec.2019.2935666openalex-snapshot
Deep Learning on Private Data
inferred← citeshttps://doi.org/10.1109/pst52912.2021.9647755openalex-snapshot
Towards Privacy-Preserving Classification-as-a-Service for DGA Detection
inferred← citeshttps://doi.org/10.1109/satml59370.2024.00029openalex-snapshot
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
inferred← citeshttps://doi.org/10.1109/seed55351.2022.00015openalex-snapshot
Establishing Cooperative Computation with Hardware Embassies
inferred← citeshttps://doi.org/10.1109/sp.2019.00045openalex-snapshot
Helen: Maliciously Secure Coopetitive Learning for Linear Models
inferred← citeshttps://doi.org/10.1109/sp40001.2021.00086openalex-snapshot
SiRnn: A Math Library for Secure RNN Inference
inferred← citeshttps://doi.org/10.1109/sp40001.2021.00098openalex-snapshot
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU
inferred← citeshttps://doi.org/10.1109/sp46214.2022.9833697openalex-snapshot
SecFloat: Accurate Floating-Point meets Secure 2-Party Computation
inferred← citeshttps://doi.org/10.1109/sp46215.2023.10179483openalex-snapshot
SoK: Cryptographic Neural-Network Computation
inferred← citeshttps://doi.org/10.1109/sp54263.2024.00101openalex-snapshot
From Individual Computation to Allied Optimization: Remodeling Privacy-Preserving Neural Inference with Function Input Tuning
inferred← citeshttps://doi.org/10.1109/sp61157.2025.00175openalex-snapshot
SHARK: Actively Secure Inference Using Function Secret Sharing
inferred← citeshttps://doi.org/10.1109/tai.2023.3247554openalex-snapshot
PpNNT: Multiparty Privacy-Preserving Neural Network Training System
inferred← citeshttps://doi.org/10.1109/tdsc.2019.2907081openalex-snapshot
Denoising in the Dark: Privacy-Preserving Deep Neural Network-Based Image Denoising
inferred← citeshttps://doi.org/10.1109/tdsc.2019.2913362openalex-snapshot
A Lightweight Privacy-Preserving CNN Feature Extraction Framework for Mobile Sensing
inferred← citeshttps://doi.org/10.1109/tdsc.2021.3074439openalex-snapshot
NN-EMD: Efficiently Training Neural Networks Using Encrypted Multi-Sourced Datasets
inferred← citeshttps://doi.org/10.1109/tdsc.2021.3139318openalex-snapshot
More Efficient Secure Matrix Multiplication for Unbalanced Recommender Systems
inferred← citeshttps://doi.org/10.1109/tdsc.2022.3168556openalex-snapshot
A Differentially Private Federated Learning Model against Poisoning Attacks in Edge Computing
inferred← citeshttps://doi.org/10.1109/tdsc.2024.3365730openalex-snapshot
EdgePro: Edge Deep Learning Model Protection via Neuron Authorization
inferred← citeshttps://doi.org/10.1109/tdsc.2024.3431590openalex-snapshot
CrossNet: A Low-Latency MLaaS Framework for Privacy-Preserving Neural Network Inference on Resource-Limited Devices
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3596652openalex-snapshot
$\mathtt {Antelope}$: Fast and Secure Neural Network Inference
inferred← citeshttps://doi.org/10.1109/tetci.2024.3367812openalex-snapshot
Exploiting Type I Adversarial Examples to Hide Data Information: A New Privacy-Preserving Approach
inferred← citeshttps://doi.org/10.1109/tifs.2022.3156818openalex-snapshot
Lightweight Privacy-Preserving GAN Framework for Model Training and Image Synthesis
inferred← citeshttps://doi.org/10.1109/tifs.2023.3262149openalex-snapshot
FastSecNet: An Efficient Cryptographic Framework for Private Neural Network Inference
inferred← citeshttps://doi.org/10.1109/tifs.2023.3265342openalex-snapshot
FlexBNN: Fast Private Binary Neural Network Inference With Flexible Bit-Width
inferred← citeshttps://doi.org/10.1109/tifs.2023.3287072openalex-snapshot
Efficient Privacy-Preserving Inference Outsourcing for Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/tifs.2024.3444327openalex-snapshot
Fregata: Fast Private Inference With Unified Secure Two-Party Protocols
inferred← citeshttps://doi.org/10.1109/tifs.2025.3526063openalex-snapshot
Panther: Practical Secure Two-Party Neural Network Inference
inferred← citeshttps://doi.org/10.1109/tifs.2025.3547308openalex-snapshot
Swift: Fast Secure Neural Network Inference With Fully Homomorphic Encryption
inferred← citeshttps://doi.org/10.1109/tifs.2026.3683269openalex-snapshot
TFMD: General and Fast Secure Neural Network Inference Framework With Threshold FHE
inferred← citeshttps://doi.org/10.1109/tifs.2026.3729507openalex-snapshot
AuditML: An Efficient Publicly Auditable Privacy-Preserving Framework for Machine Learning Inference
inferred← citeshttps://doi.org/10.1109/tit.2023.3344141openalex-snapshot
Order Optimal Bounds for One-Shot Federated Learning Over Non-Convex Loss Functions
inferred← citeshttps://doi.org/10.1109/tits.2022.3149600openalex-snapshot
PrivacySignal: Privacy-Preserving Traffic Signal Control for Intelligent Transportation System
inferred← citeshttps://doi.org/10.1109/tkde.2023.3321803openalex-snapshot
Cryptographic Primitives in Privacy-Preserving Machine Learning: A Survey
inferred← citeshttps://doi.org/10.1109/tmc.2025.3551368openalex-snapshot
Exploring Communication-Efficient Federated Learning via Stateless in-Network Aggregation
inferred← citeshttps://doi.org/10.1109/tmi.2024.3377248openalex-snapshot
MP-Net: A Multi-Center Privacy-Preserving Network for Medical Image Segmentation
inferred← citeshttps://doi.org/10.1109/tnse.2020.3040704openalex-snapshot
SecureTrain: An Approximation-Free and Computationally Efficient Framework for Privacy-Preserved Neural Network Training
inferred← citeshttps://doi.org/10.1109/tnse.2022.3177755openalex-snapshot
PCNNCEC: Efficient and Privacy-Preserving Convolutional Neural Network Inference Based on Cloud-Edge-Client Collaboration
inferred← citeshttps://doi.org/10.1109/tnse.2025.3534834openalex-snapshot
EPCNN: Efficient and Practical Privacy-Preserving Convolutional Neural Network Inference
inferred← citeshttps://doi.org/10.1109/tnsm.2024.3399534openalex-snapshot
Dual-Server-Based Lightweight Privacy-Preserving Federated Learning
inferred← citeshttps://doi.org/10.1109/tps-isa50397.2020.00038openalex-snapshot
Revisiting Secure Computation Using Functional Encryption: Opportunities and Research Directions
inferred← citeshttps://doi.org/10.1109/tpsisa52974.2021.00003openalex-snapshot
Towards Faster Functional Encryption for Privacy-preserving Machine Learning
inferred← citeshttps://doi.org/10.1109/tsc.2023.3349298openalex-snapshot
Privacy-Preserving Convolutional Neural Network Classification Scheme With Multiple Keys
inferred← citeshttps://doi.org/10.1109/tsc.2025.3586091openalex-snapshot
Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage
inferred← citeshttps://doi.org/10.1109/tvlsi.2022.3197895openalex-snapshot
Efficient Homomorphic Convolution Designs on FPGA for Secure Inference
inferred← citeshttps://doi.org/10.1109/vts.2019.8758660openalex-snapshot
Leveraging Memory PUFs and PIM-based encryption to secure edge deep learning systems
inferred← citeshttps://doi.org/10.1109/wifs.2018.8630790openalex-snapshot
Privacy-Preserving Distributed Deep Learning with Privacy Transformations
inferred← citeshttps://doi.org/10.1145/3133956.3134056openalex-snapshot
Oblivious Neural Network Predictions via MiniONN Transformations
inferred← citeshttps://doi.org/10.1145/3240765.3274560openalex-snapshot
Privacy-preserving deep learning and inference
inferred← citeshttps://doi.org/10.1145/3292006.3300044openalex-snapshot
Deep Neural Networks Classification over Encrypted Data
inferred← citeshttps://doi.org/10.1145/3314221.3314628openalex-snapshot
CHET: an optimizing compiler for fully-homomorphic neural-network inferencing
inferred← citeshttps://doi.org/10.1145/3338466.3358919openalex-snapshot
Secure and Private Function Evaluation with Intel SGX
inferred← citeshttps://doi.org/10.1145/3394658openalex-snapshot
Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics
inferred← citeshttps://doi.org/10.1145/3548606.3560709openalex-snapshot
Private and Reliable Neural Network Inference
inferred← citeshttps://doi.org/10.1145/3607192openalex-snapshot
Scalable Binary Neural Network Applications in Oblivious Inference
inferred← citeshttps://doi.org/10.1155/2022/9983463openalex-snapshot
Privacy-Preserving Outsourcing Scheme for SVM on Vertically Partitioned Data
inferred← citeshttps://doi.org/10.12794/metadc1703277openalex-snapshot
Privacy Preserving Machine Learning as a Service
inferred← citeshttps://doi.org/10.1371/journal.pone.0272423openalex-snapshot
Secure deep learning for distributed data against malicious central server
inferred← citeshttps://doi.org/10.14722/ndss.2019.23119openalex-snapshot
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
inferred← citeshttps://doi.org/10.14722/ndss.2021.24351openalex-snapshot
GALA: Greedy ComputAtion for Linear Algebra in Privacy-Preserved Neural Networks
inferred← citeshttps://doi.org/10.1587/transfun.2019dmi0001openalex-snapshot
Recent Advances in Practical Secure Multi-Party Computation
inferred← citeshttps://doi.org/10.1587/transfun.2020tap0011openalex-snapshot
Efficient Secure Neural Network Prediction Protocol Reducing Accuracy Degradation
inferred← citeshttps://doi.org/10.1609/aaai.v38i15.29620openalex-snapshot
United We Stand: Accelerating Privacy-Preserving Neural Inference by Conjunctive Optimization with Interleaved Nexus
inferred← citeshttps://doi.org/10.18653/v1/2021.emnlp-main.156openalex-snapshot
CRYPTOGRU: Low Latency Privacy-Preserving Text Analysis With GRU
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2910088/v1openalex-snapshot
PAF-FHE: Low-Cost Accurate Non-Polynomial Operator Polynomial Approximation in Fully Homomorphic Encryption Based ML Inference
inferred← citeshttps://doi.org/10.21437/interspeech.2018-2032openalex-snapshot
VoiceGuard: Secure and Private Speech Processing
inferred← citeshttps://doi.org/10.2147/jmdh.s483247openalex-snapshot
TinyML-Based Lightweight AI Healthcare Mobile Chatbot Deployment
inferred← citeshttps://doi.org/10.2172/1737477openalex-snapshot
Considerations for using Privacy Preserving Machine Learning Techniques for Safeguards
inferred← citeshttps://doi.org/10.2196/preprints.52111openalex-snapshot
Proposing a person-centred decentralised health data ecosystem to optimise applied data science and artificial intelligence for dementia prevention and cognitive longevity. (Preprint)
inferred← citeshttps://doi.org/10.2197/ipsjjip.31.667openalex-snapshot
A Study on Quantized Parameters for Protection of a Model and Its Inference Input
inferred← citeshttps://doi.org/10.23919/date56975.2023.10137048openalex-snapshot
SPHERE-DNA: Privacy-Preserving Federated Learning for eHealth
inferred← citeshttps://doi.org/10.2478/popets-2020-0077openalex-snapshot
Secure Evaluation of Quantized Neural Networks
inferred← citeshttps://doi.org/10.24963/ijcai.2019/668openalex-snapshot
Novel Collaborative Filtering Recommender Friendly to Privacy Protection
inferred← citeshttps://doi.org/10.32604/jihpp.2021.026944openalex-snapshot
Verifiable Privacy-Preserving Neural Network on Encrypted Data
inferred← citeshttps://doi.org/10.3389/fdata.2021.729663openalex-snapshot
A Systematic Review on Model Watermarking for Neural Networks
inferred← citeshttps://doi.org/10.3390/electronics14050985openalex-snapshot
Communication Efficient Secure Three-Party Computation Using Lookup Tables for RNN Inference
inferred← citeshttps://doi.org/10.3390/electronics8040411openalex-snapshot
Privacy-Preserving Distributed Deep Learning via Homomorphic Re-Encryption
inferred← citeshttps://doi.org/10.3390/math11041048openalex-snapshot
A Study of Privacy-Preserving Neural Network Prediction Based on Replicated Secret Sharing
inferred← citeshttps://doi.org/10.35784/acs_7397openalex-snapshot
Enhanced IoT cybersecurity through Machine Learning - based penetration testing
inferred← citeshttps://doi.org/10.36227/techrxiv.170956580.07799070/v1openalex-snapshot
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey
inferred← citeshttps://doi.org/10.3837/tiis.2021.12.005openalex-snapshot
Privacy-preserving and Communication-efficient Convolutional Neural Network Prediction Framework in Mobile Cloud Computing
inferred← citeshttps://doi.org/10.46586/tches.v2025.i1.420-449openalex-snapshot
Dash: Accelerating Distributed Private Convolutional Neural Network Inference with Arithmetic Garbled Circuits
inferred← citeshttps://doi.org/10.48550/arxiv.1710.01727openalex-snapshot
Privacy-Preserving Deep Inference for Rich User Data on The Cloud
inferred← citeshttps://doi.org/10.48550/arxiv.1801.03239openalex-snapshot
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications
inferred← citeshttps://doi.org/10.48550/arxiv.1802.02432openalex-snapshot
CryptoRec: Privacy-preserving Recommendation as a Service
inferred← citeshttps://doi.org/10.48550/arxiv.1806.03461openalex-snapshot
TAPAS : tricks to accelerate (encrypted) prediction as a service
inferred← citeshttps://doi.org/10.48550/arxiv.1812.00564openalex-snapshot
Split learning for health: Distributed deep learning without sharing raw patient data
inferred← citeshttps://doi.org/10.48550/arxiv.1902.04885openalex-snapshot
Federated Machine Learning: Concept and Applications
inferred← citeshttps://doi.org/10.48550/arxiv.1908.07701openalex-snapshot
A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component
inferred← citeshttps://doi.org/10.48550/arxiv.2004.12254openalex-snapshot
Privacy in Deep Learning: A Survey
inferred← citeshttps://doi.org/10.48550/arxiv.2006.04747openalex-snapshot
Secure Byzantine-Robust Machine Learning
inferred← citeshttps://doi.org/10.5121/csit.2020.10110openalex-snapshot
Computer Science & Information Technology (CS & IT)
inferred← citeshttps://doi.org/10.5121/csit.2020.101120openalex-snapshot
Survey on Federated Learning Towards Privacy Preserving AI
inferred← citeshttps://doi.org/10.5220/0009829603970404openalex-snapshot
ProteiNN: Privacy-preserving One-to-Many Neural Network Classifications
inferred← citeshttps://doi.org/10.5220/0009890704970504openalex-snapshot
SwaNN: Switching among Cryptographic Tools for Privacy-preserving Neural Network Predictions
inferred← citeshttps://doi.org/10.56553/popets-2022-0109openalex-snapshot
LLAMA: A Low Latency Math Library for Secure Inference
inferred← citeshttps://doi.org/10.56553/popets-2022-0113openalex-snapshot
Pika: Secure Computation using Function Secret Sharing over Rings
inferred← citeshttps://doi.org/10.56553/popets-2022-0131openalex-snapshot
Adam in Private: Secure and Fast Training of Deep Neural Networks with Adaptive Moment Estimation
inferred← citeshttps://doi.org/10.5772/intechopen.111477openalex-snapshot
Introductory Chapter: Data Privacy Preservation on the Internet of Things
inferred← citeshttps://doi.org/10.70675/f2b18e62z1092z4868z93a3z9765eff3e668openalex-snapshot
Privacy-preserving machine learning techniques
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