The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Data security concurrent with homogeneous by AES algorithm in SSD controller
Open accessAbstract
AES has been one of the most popular encryption and decryption algorithms for data security applications. At the same time, data randomization (or “homogeneous”) technology was applied to reduce the bit error rate (BER) of MLC and TLC flash memory. Here, AES algorithm was found efficient to replace the orthogonal polynomials which normally carry out homogeneous function by scrambling data. This paper put forward a novel hardware architecture providing both homogeneous and data encryption/decryption functions concurrently by an embedded AES hardware engine while getting rid of randomization engine with Linear Feedback Shift Register (LFSR). It made a flash controller simple and reduced the die size because the independent homogeneous hard engine is no longer necessary for a flash memory system, in which AES security algorithm embedded. Finally a SSD controller designed in this architecture was silicon proven.
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“The detection accuracy of Faster R-CNN is higher than SSD [32, 33], Fast R-CNN [34], and other algorithms verified on multiple datasets.”
From A New Steel Defect Detection Algorithm Based on Deep Learning (2021) · cites this paper as [33]
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Citations
Cites
Shift-register synthesis and BCH decoding
Massey, J. L. (1969) · IEEE Transactions on Information Theory · doi:10.1109/tit.1969.1054260 · Cited by 2,213
Recommendation for block cipher modes of operation: methods and techniques
Dworkin, M. J. (2001) · doi:10.6028/nist.sp.800-38a · Cited by 746
The Art of Error Correcting Coding
Morelos-Zaragoza, R. H. (2006) · Wiley eBooks · doi:10.1002/0470035706 · Cited by 319
Cited by
Sorted by citations
A New Steel Defect Detection Algorithm Based on Deep Learning
Zhao, W., Chen, F., Huang, H., Li, D., & Cheng, W. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/5592878 · Cited by 259
“Faster R-CNN is the mainstream two-stage target detection algorithm, which is used in face detection and defect detection widely. detection accuracy of Faster R-CNN is higher than SSD [32, 33], Fast R-CNN [34], and other algorithms verified on multiple datasets.”
Method
Metadata
- Authors
- Fan, L., Luo, J., Liu, H., & Geng, X.
- Affiliations
- Hangzhou Dianzi University (CN)
- Sage Microelectronics Corporation
- Shanghai Maritime University (CN)
- Venue
- IEICE Electronics Express
- Published
- 2014
- Volume
- 11
- Issue
- 13
- Pages
- 20140535-20140535
- ISSN
- 1349-2543 (ISSN-L)
- OpenAlex
- W2072644400
- Cited by
- 7
- References
- 3
- Citations by year
- 2025: 1 · 2023: 1 · 2021: 2 · 2019: 1 · 2018: 1 · 2015: 1
- FWCI
- 0.33
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IEICE Electronics Express (publishedVersion)
- Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Zhejiang Province
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Data Storage Technologies
- Physical Sciences › Mathematics › Discrete Mathematics and Combinatorics › Coding theory and cryptography
- Keywords
- AES, flash memory, data randomization, data encryption, hardware architecture, linear feedback shift registers, bit error rate reduction
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