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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Xiao, Chunhua | en |
dc.contributor.author | Zhang, Lei | en |
dc.contributor.author | Liu, Weichen | en |
dc.contributor.author | Bergmann, Neil | en |
dc.contributor.author | Li, Pengda | en |
dc.date.accessioned | 2018-08-30T06:41:25Z | en |
dc.date.accessioned | 2019-12-06T17:02:06Z | - |
dc.date.available | 2018-08-30T06:41:25Z | en |
dc.date.available | 2019-12-06T17:02:06Z | - |
dc.date.issued | 2018 | en |
dc.identifier.citation | Xiao, C., Li, P., Zhang, L., Liu, W., & Bergmann, N. (2018). ACA-SDS : adaptive crypto acceleration for secure data storage in big data. IEEE Access, in press. doi:10.1109/ACCESS.2018.2862425 | en |
dc.identifier.uri | https://hdl.handle.net/10356/88385 | - |
dc.description.abstract | In the era of Big Data, the demand for secure data storage is rapidly increasing. To accelerate the complex encryption computation, both specific instructions and hardware accelerators are adopted in a large number of scenarios. However, the hardware accelerators are not so effective especially for small volume data due to the induced invocation costs, while the AES-NI (Intel® Advanced Encryption Standard New Instructions) is not so energy efficiency for big data. To satisfy the diversity performance/energy requirements for intensive data encryptions, a collaborative solution is proposed in this work. We proposed a feasible hardware-software co-design methodology based on the stack file system eCryptfs, with QAT (Quick Assist Technology), which is named as ACA-SDS: Adaptive Crypto Acceleration for Secure Data Storage. ACA-SDS is able to choose the optimal encryption solution dynamically according to file operation modes and request characters. Adjustable parameters, such as α, β and M are provided in our scheme to provide a better adaptability and trade-off choices for encryption computation. Our evaluation shows that ACA-SDS can get 15%-25% performance improvement for big-data blocks compared with only software or hardware accelerations. Furthermore, our methodology provides a wide range of practical design concepts for the further research in this field. | en |
dc.format.extent | 12 p. | en |
dc.language.iso | en | en |
dc.relation.ispartofseries | IEEE Access | en |
dc.rights | © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. | en |
dc.subject | Encryption | en |
dc.subject | Hardware-Software Co-design | en |
dc.subject | DRNTU::Engineering::Computer science and engineering | en |
dc.title | ACA-SDS : adaptive crypto acceleration for secure data storage in big data | en |
dc.type | Journal Article | en |
dc.contributor.school | School of Computer Science and Engineering | en |
dc.identifier.doi | 10.1109/ACCESS.2018.2862425 | en |
dc.description.version | Published version | en |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | SCSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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ACA-SDS adaptive crypto acceleration for secure data storage in big data.pdf | 850.16 kB | Adobe PDF | View/Open |
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