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10/16/2022
Accelerating Transfer Learning with Near-Data Computation on Cloud Object Stores
Near-data computation techniques have been successfully deployed to miti...
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05/12/2022
Synergia: Hardening High-Assurance Security Systems with Confidential and Trusted Computing
High-assurance security systems require strong isolation from the untrus...
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10/03/2021
SecFL: Confidential Federated Learning using TEEs
Federated Learning (FL) is an emerging machine learning paradigm that en...
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04/30/2021
WELES: Policy-driven Runtime Integrity Enforcement of Virtual Machines
Trust is of paramount concern for tenants to deploy their security-sensi...
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03/31/2021
Perun: Secure Multi-Stakeholder Machine Learning Framework with GPU Support
Confidential multi-stakeholder machine learning (ML) allows multiple par...
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01/20/2021
secureTF: A Secure TensorFlow Framework
Data-driven intelligent applications in modern online services have beco...
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01/05/2021
A practical approach for updating an integrity-enforced operating system
Trusted computing defines how to securely measure, store, and verify the...
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12/11/2020
TEEMon: A continuous performance monitoring framework for TEEs
Trusted Execution Environments (TEEs), such as Intel Software Guard eXte...
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03/31/2020
Trust Management as a Service: Enabling Trusted Execution in the Face of Byzantine Stakeholders
Trust is arguably the most important challenge for critical services bot...
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02/12/2019
TensorSCONE: A Secure TensorFlow Framework using Intel SGX
Machine learning has become a critical component of modern data-driven o...
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05/15/2018
Approximate Distributed Joins in Apache Spark
The join operation is a fundamental building block of parallel data proc...
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05/15/2018