- 著者
- Lingyan Fan Jianjun Luo Hailuan Liu Xuan Geng
- 出版者
- The Institute of Electronics, Information and Communication Engineers
- 雑誌
- IEICE Electronics Express (ISSN:13492543)
- 巻号頁・発行日
- vol.11, no.13, pp.20140535-20140535, 2014 (Released:2014-07-10)
- 参考文献数
- 6
- 被引用文献数
- 3
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.
- 著者
- Weiwei LUO Wenpeng ZHOU Jinglong FANG Lingyan FAN
- 出版者
- The Institute of Electronics, Information and Communication Engineers
- 雑誌
- IEICE Transactions on Information and Systems (ISSN:09168532)
- 巻号頁・発行日
- vol.E105.D, no.1, pp.180-183, 2022-01-01 (Released:2022-01-01)
- 参考文献数
- 10
Recently, channel-aware steganography has been presented for high security. The corresponding selection-channel-aware (SCA) detecting algorithms have also been proposed for improving the detection performance. In this paper, we propose a novel detecting algorithm of JPEG steganography, where the embedding probability and block evaluation are integrated into the new probability. This probability can embody the change due to data embedding. We choose the same high-pass filters as maximum diversity cascade filter residual (MD-CFR) to obtain different image residuals and a weighted histogram method is used to extract detection features. Experimental results on detecting two typical steganographic methods show that the proposed method can improve the performance compared with the state-of-art methods.