Abstract
Growing use of cloud raises privacy concerns for search in sensitive databases such as bioinformatics, where homomorphic encryption can help through direct computation -hence search/pattern matching-on the encrypted data. The recently proposed homomorphic secure content-addressable memory (SCAM) exploits this principle. Data dependencies in SCAM, however, lead to a memory bottleneck which has been addressed by various near-memory computing solutions. In this paper we demonstrate a more efficient alternative based on the true in-memory computing substrate spintronic Computational RAM (CRAM). The resulting SCAM accelerator, H-CRAM, achieves significant speedup and energy reduction.
Original language | English (US) |
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Title of host publication | Proceedings - 2021 International Symposium on Secure and Private Execution Environment Design, SEED 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 70-75 |
Number of pages | 6 |
ISBN (Electronic) | 9781665420259 |
DOIs | |
State | Published - 2021 |
Event | 1st International Symposium on Secure and Private Execution Environment Design, SEED 2021 - Virtual, Online, United States Duration: Sep 20 2021 → Sep 21 2021 |
Publication series
Name | Proceedings - 2021 International Symposium on Secure and Private Execution Environment Design, SEED 2021 |
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Conference
Conference | 1st International Symposium on Secure and Private Execution Environment Design, SEED 2021 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 9/20/21 → 9/21/21 |
Bibliographical note
Funding Information:This work was supportedACKNOWinLEDGMENTpart by NSF grant no. SPX-1725420.
Publisher Copyright:
© 2021 IEEE.
Keywords
- Computational RAM
- Homomorphic
- Processing in Memory