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TEESlice : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models
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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/cpe.4130openalex-snapshot
A framework for application partitioning using trusted execution environments
inferredcites →https://doi.org/10.1007/978-1-4612-4380-9openalex-snapshot
Breakthroughs in Statistics
inferredcites →https://doi.org/10.1007/978-1-4612-4380-9_16openalex-snapshot
Individual Comparisons by Ranking Methods
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/978-3-319-28865-9_40openalex-snapshot
Securing Application with Software Partitioning: A Case Study Using SGX
inferredcites →https://doi.org/10.1016/j.cose.2023.103180openalex-snapshot
A survey on the (in)security of trusted execution environments
inferredcites →https://doi.org/10.1109/ccgrid49817.2020.00-41openalex-snapshot
Serdab: An IoT Framework for Partitioning Neural Networks Computation across Multiple Enclaves
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.463openalex-snapshot
Age Progression/Regression by Conditional Adversarial Autoencoder
inferredcites →https://doi.org/10.1109/cvpr.2019.00316openalex-snapshot
NetTailor: Tuning the Architecture, Not Just the Weights
inferredcites →https://doi.org/10.1109/cvpr.2019.00509openalex-snapshot
Knockoff Nets: Stealing Functionality of Black-Box Models
inferredcites →https://doi.org/10.1109/cvprw53098.2021.00368openalex-snapshot
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
inferredcites →https://doi.org/10.1109/dac.2018.8465773openalex-snapshot
Reverse Engineering Convolutional Neural Networks Through Side-channel Information Leaks
inferredcites →https://doi.org/10.1109/eurosp.2019.00044openalex-snapshot
PRADA: Protecting Against DNN Model Stealing Attacks
inferredcites →https://doi.org/10.1109/icassp48485.2024.10446717openalex-snapshot
A Fast, Performant, Secure Distributed Training Framework For LLM
inferredcites →https://doi.org/10.1109/iccad57390.2023.10323746openalex-snapshot
MirrorNet: A TEE-Friendly Framework for Secure On-Device DNN Inference
inferredcites →https://doi.org/10.1109/iccmc56507.2023.10084208openalex-snapshot
A Review on the Potential of AI Voice Assistants for Personalized and Adaptive Learning in Education
inferredcites →https://doi.org/10.1109/icse48619.2023.00049openalex-snapshot
FedSlice: Protecting Federated Learning Models from Malicious Participants with Model Slicing
inferredcites →https://doi.org/10.1109/jproc.2020.3004555openalex-snapshot
A Comprehensive Survey on Transfer Learning
inferredcites →https://doi.org/10.1109/msec.2019.2963021openalex-snapshot
SgxPectre: Stealing Intel Secrets From SGX Enclaves via Speculative Execution
inferredcites →https://doi.org/10.1109/rtss52674.2021.00018openalex-snapshot
AegisDNN: Dependable and Timely Execution of DNN Tasks with SGX
inferredcites →https://doi.org/10.1109/sp.2015.29openalex-snapshot
ObliVM: A Programming Framework for Secure Computation
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2018.00024openalex-snapshot
Racing in Hyperspace: Closing Hyper-Threading Side Channels on SGX with Contrived Data Races
inferredcites →https://doi.org/10.1109/sp.2019.00002openalex-snapshot
Spectre Attacks: Exploiting Speculative Execution
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/sp.2019.00087openalex-snapshot
RIDL: Rogue In-Flight Data Load
inferredcites →https://doi.org/10.1109/sp40000.2020.00057openalex-snapshot
Plundervolt: Software-based Fault Injection Attacks against Intel SGX
inferredcites →https://doi.org/10.1109/sp40001.2021.00063openalex-snapshot
PLATYPUS: Software-based Power Side-Channel Attacks on x86
inferredcites →https://doi.org/10.1109/sp46214.2022.9833607openalex-snapshot
Model Stealing Attacks Against Inductive Graph Neural Networks
inferredcites →https://doi.org/10.1109/sp46214.2022.9833649openalex-snapshot
Membership Inference Attacks From First Principles
inferredcites →https://doi.org/10.1109/sp46214.2022.9833743openalex-snapshot
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories
inferredcites →https://doi.org/10.1109/sp46214.2022.9833747openalex-snapshot
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models
inferredcites →https://doi.org/10.1109/sp46214.2022.9833768openalex-snapshot
A Systematic Look at Ciphertext Side Channels on AMD SEV-SNP
inferredcites →https://doi.org/10.1109/sp54263.2024.00052openalex-snapshot
No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML
inferredcites →https://doi.org/10.1109/spw.2019.00020openalex-snapshot
Defending Against Neural Network Model Stealing Attacks Using Deceptive Perturbations
inferredcites →https://doi.org/10.1109/tdsc.2021.3088480openalex-snapshot
Leveraging Domain Adaptation as a Defense Against Membership Inference Attacks
inferredcites →https://doi.org/10.1109/tdsc.2021.3126315openalex-snapshot
Model Protection: Real-Time Privacy-Preserving Inference Service for Model Privacy at the Edge
inferredcites →https://doi.org/10.1109/tdsc.2022.3174569openalex-snapshot
Defending Against Membership Inference Attacks With High Utility by GAN
inferredcites →https://doi.org/10.1109/tdsc.2023.3334277openalex-snapshot
Building a Lightweight Trusted Execution Environment for Arm GPUs
inferredcites →https://doi.org/10.1109/vlsi-soc.2014.7004182openalex-snapshot
Electromagnetic analysis and fault injection onto secure circuits
inferredcites →https://doi.org/10.1145/1273496openalex-snapshot
Proceedings of the 24th international conference on Machine learning
inferredcites →https://doi.org/10.1145/2487726.2488368openalex-snapshot
Innovative instructions and software model for isolated execution
inferredcites →https://doi.org/10.1145/3052973.3053009openalex-snapshot
Practical Black-Box Attacks against Machine Learning
inferredcites →https://doi.org/10.1145/3133956.3134038openalex-snapshot
Leaky Cauldron on the Dark Land
inferredcites →https://doi.org/10.1145/3243734.3243855openalex-snapshot
Machine Learning with Membership Privacy using Adversarial Regularization
inferredcites →https://doi.org/10.1145/3368089.3409676openalex-snapshot
Dynamic slicing for deep neural networks
inferredcites →https://doi.org/10.1145/3372297.3417270openalex-snapshot
Information Leakage in Embedding Models
inferredcites →https://doi.org/10.1145/3456631openalex-snapshot
Security Vulnerabilities of SGX and Countermeasures
inferredcites →https://doi.org/10.1145/3460120.3484575openalex-snapshot
Membership Leakage in Label-Only Exposures
inferredcites →https://doi.org/10.1145/3460120.3484756openalex-snapshot
When Machine Unlearning Jeopardizes Privacy
inferredcites →https://doi.org/10.1145/3466752.3480112openalex-snapshot
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware
inferredcites →https://doi.org/10.1145/3523273openalex-snapshot
Membership Inference Attacks on Machine Learning: A Survey
inferredcites →https://doi.org/10.1145/3536168.3543299openalex-snapshot
TEESlice: slicing DNN models for secure and efficient deployment
inferredcites →https://doi.org/10.1145/3576915.3624398openalex-snapshot
Poster: Towards Lightweight TEE-Assisted MPC
inferredcites →https://doi.org/10.1145/3620667openalex-snapshot
Defenses to Membership Inference Attacks: A Survey
inferredcites →https://doi.org/10.1145/3658644openalex-snapshot
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security
inferredcites →https://doi.org/10.14722/ndss.2017.23193openalex-snapshot
T-SGX: Eradicating Controlled-Channel Attacks Against Enclave Programs
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.2022.24173openalex-snapshot
Hybrid Trust Multi-party Computation with Trusted Execution Environment
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1561/9781601988195openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1609/aaai.v35i17.17746openalex-snapshot
Goten: GPU-Outsourcing Trusted Execution of Neural Network Training
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.703openalex-snapshot
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
inferredcites →https://doi.org/10.48550/arxiv.2305.15986openalex-snapshot
ACAI: Protecting Accelerator Execution with Arm Confidential Computing Architecture
inferredcites →https://doi.org/10.56553/popets-2022-0105openalex-snapshot
3LegRace: Privacy-Preserving DNN Training over TEEs and GPUs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-97623-0_2openalex-snapshot
InferONNX: Practical and Privacy-Preserving Machine Learning Inference Using Trusted Execution Environments
inferred← citeshttps://doi.org/10.1007/978-3-032-34377-2_24openalex-snapshot
Locki: Neural Networks That Only Behave When Unlocked via Runtime Decryption
inferred← citeshttps://doi.org/10.1007/978-981-95-6963-2_4openalex-snapshot
Backdoor-Based Protection Framework for Model Functional Services
inferred← citeshttps://doi.org/10.1007/s10664-025-10750-xopenalex-snapshot
TransLock: Securing LLM deployment for software applications via self-locking watermarks
inferred← citeshttps://doi.org/10.1080/00295639.2025.2594881openalex-snapshot
Regression Analysis with the Directed Infusion of Data
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/icassp55912.2026.11462929openalex-snapshot
CorrEctor: An Execute-to-Correct Paradigm for Efficient LLM Secure Inference
inferred← citeshttps://doi.org/10.1109/isqed69900.2026.11534707openalex-snapshot
CELLM: Confidential and Efficient Lightweight LLM Inference in TEEs
inferred← citeshttps://doi.org/10.1109/lca.2025.3555183openalex-snapshot
Exploiting Intel AMX Power Gating
inferred← citeshttps://doi.org/10.1109/ojcoms.2026.3680064openalex-snapshot
LLMs and IoT: A Comprehensive Survey on Large Language Models and the Internet of Things
inferred← citeshttps://doi.org/10.1109/srds69199.2025.00021openalex-snapshot
ENSI: Efficient Non-Interactive Secure Inference for Large Language Models
inferred← citeshttps://doi.org/10.1109/tccn.2025.3612760openalex-snapshot
Toward Edge General Intelligence With Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration
inferred← citeshttps://doi.org/10.1109/tdsc.2026.3677485openalex-snapshot
Towards Efficient and Reliable Training Assurance of Untrusted Federated Learning Participants Under Hardware Non-Determinism
inferred← citeshttps://doi.org/10.1109/tii.2025.3593981openalex-snapshot
AI-Auditor: A Data Auditing Framework for Enhancing the Trustworthiness of AI Models
inferred← citeshttps://doi.org/10.1145/3731556openalex-snapshot
NeuSemSlice: Towards Effective DNN Model Maintenance via Neuron-Level Semantic Slicing
inferred← citeshttps://doi.org/10.1145/3799230openalex-snapshot
LLMGuard : Safeguarding Real-Time Inference for Large Language Models on Edge Devices
inferred← citeshttps://doi.org/10.1145/3807455openalex-snapshot
Foundation Models for Autonomous Driving Systems: An Initial Roadmap
inferred← citeshttps://doi.org/10.1360/ssi-2025-0248openalex-snapshot
DMS-MIA: disk replay-based and multi-metric sequence membership inference attack on TEE-protected machine learning models
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