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<scp>TEESlice</scp> : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models
Research article (ACM Transactions on Software Engineering and Methodology, 2024) · cited 13× · AI/ML
TEESlice : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models
Summary
TEESlice : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models is a scholarly article[1].
Key Facts
TEESlice : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). <scp>TEESlice</scp> : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/scp-teeslice-scp-protecting-sensitive-neural-network-models-in-trusted-execution-environments-when-attackers-have-pre-tr
MLA“<scp>TEESlice</scp> : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/scp-teeslice-scp-protecting-sensitive-neural-network-models-in-trusted-execution-environments-when-attackers-have-pre-tr.
BibTeX@misc{4ortxyz_scp-teeslice-scp-protecting-sensitive-neural-network-models-in-trusted-execution-environments-when-attackers-have-pre-tr_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{<scp>TEESlice</scp> : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models}}, year = {2026}, url = {https://4ort.xyz/entity/scp-teeslice-scp-protecting-sensitive-neural-network-models-in-trusted-execution-environments-when-attackers-have-pre-tr}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): <scp>TEESlice</scp> : Protecting Sensitive Neural Network Models in Trusted Execution Environments when Attackers Have Pre-Trained Models — https://4ort.xyz/entity/scp-teeslice-scp-protecting-sensitive-neural-network-models-in-trusted-execution-environments-when-attackers-have-pre-tr (retrieved 2026-05-24)
