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James Pangia

dblp:373/2523 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Hardware security and side channels · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware security and side channels › memory integrity
integrity tree
0.812024
Data Enclave: A Data-Centric Trusted Execution Environment · HPCA 2024
Hardware security and side channels › trusted execution environments
secure enclaves
0.812024
Data Enclave: A Data-Centric Trusted Execution Environment · HPCA 2024
Hardware security and side channels
trusted execution environments
0.812024
Data Enclave: A Data-Centric Trusted Execution Environment · HPCA 2024

Methods — techniques the papers use, named apart from their topics

secure permission control · 0.8cryptographic isolation · 0.8
YearPublicationVenuePosition
2024 Data Enclave: A Data-Centric Trusted Execution Environment
abstract
Trusted Execution Environments (TEEs) protect sensitive applications in the cloud with the minimal trust in the cloud provider. Existing TEEs with integrity protection however lack support for data management primitives, causing data sharing between enclaves either insecure or cumbersome. This paper proposes a new data abstraction for TEEs, data enclave. As a data-centric abstraction, data enclave is decoupled from an enclave's existence, is equipped with flexible secure permission controls, and crytographically isolated. It eliminates the hurdles for enclaves to cooperate efficiently, and at the same time, enables dynamic shrinking of the height of integrity tree for performance. This paper presents this new abstraction, its properties, and the architecture support. Experiments on synthetic benchmarks and three real-world applications all show that data enclave can help improve the efficiency of enclaves and inter-enclave cooperations significantly while enhancing the security protection.
Yuanchao Xu 0001, James Pangia, Chencheng Ye 0001, Yan Solihin, Xipeng Shen
HPCA2