본문 바로가기 주메뉴 바로가기
22대 대한민국 국회 국회정보길라잡이 국회의원검색
회원가입 로그인
HOME

정보검색

소장정보 검색

국회도서관 홈으로 정보검색 소장정보 검색
결과 내 검색 동의어 포함
결과 내 검색 동의어 포함

-

초록보기

Due to the explosive growth of multimedia speech data, how to protect the privacy of speech data and how to efficiently retrieve speech data have become a hot spot for researchers in recent years. In this paper, we proposed an encrypted speech retrieval scheme based on long short-term memory (LSTM) neural network and deep hashing. This scheme not only achieves efficient retrieval of massive speech in cloud environment, but also effectively avoids the risk of sensitive information leakage. Firstly, a novel speech encryption algorithm based on 4D quadratic autonomous hyperchaotic system is proposed to realize the privacy and security of speech data in the cloud. Secondly, the integrated LSTM network model and deep hashing algorithm are used to extract high-level features of speech data. It is used to solve the high dimensional and temporality problems of speech data, and increase the retrieval efficiency and retrieval accuracy of the proposed scheme. Finally, the normalized Hamming distance algorithm is used to achieve matching. Compared with the existing algorithms, the proposed scheme has good discrimination and robustness and it has high recall, precision and retrieval efficiency under various content preserving operations. Meanwhile, the proposed speech encryption algorithm has high key space and can effectively resist exhaustive attacks.

권호기사

권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
A reusable SQL injection detection method for Java Web applications Chengwan He, Yue He p. 2576-2590
RPSMDSM : residential power scheduling and modelling for demand side management Sheeraz Ahmed, Ali Raza, Shahryar Shafique, Mukhtar Ahmad, M.Yousaf Ali Khan, Asif Nawaz, Rohi Tariq p. 2398-2421
ASSVD : adaptive sparse singular value decomposition for high dimensional matrices Xiucai Ding, Xianyi Chen, Mengling Zou, Guangxing Zhang p. 2634-2648
Auxiliary stacked denoising autoencoder based collaborative filtering recommendation Ruihui Mu, Xiaoqin Zeng p. 2310-2332
Prioritized data transmission mechanism for IoT Changsu Jung p. 2333-2353
A robust and device-free daily activities recognition system using Wi-Fi signals Enjie Ding, Yue Zhang, Yun Xin, Lei Zhang, Yu Huo, Yafeng Liu p. 2377-2397
Video saliency detection using Bi-directional LSTM Yang Chi, Jinjiang Li p. 2444-2463
Low-dose CT image denoising using classification densely connected residual network Jun Ming, Benshun Yi, Yungang Zhang, Huixin Li p. 2480-2496
Energy-efficient resource allocation for application including dependent tasks in mobile edge computing Yang Li, Gaochao Xu, Jiaqi Ge, Peng Liu, Xiaodong Fu p. 2422-2443
A data hiding scheme based on turtle-shell for AMBTC compressed images Chin-Feng Lee, Chin-Chen Chang, Guan-Long Li p. 2554-2575
Energy efficiency maximization for energy harvesting bidirectional cooperative sensor networks with AF mode Siyang Xu, Xin Song, Lin Xia, Zhigang Xie p. 2686-2708
Subjective evaluation of ultra-high definition (UHD) videos Tariq Rahim, Soo Young Shin p. 2464-2479
Deterministic bipolar compressed sensing matrices from binary sequence family Cunbo Lu, Wengu Chen, Haibo Xu p. 2497-2517
An encrypted speech retrieval scheme based on long short-term memory neural network and deep hashing Qiu-yu Zhang, Yu-zhou Li, Ying-jie Hu p. 2612-2633
An adaptive key redistribution method for filtering-based wireless sensor networks Jin Myoung Kim, Hae Young Lee p. 2518-2533
Adaptive k-means clustering for flying Ad-hoc networks Ali Raza, Muhammad Fahad Khan, Muazzam Maqsood, Bilal Haider, Farhan Aadil p. 2670-2685
Provably secure certificateless encryption scheme in the standard model Lunzhi Deng, Tian Xia, Xiuru He p. 2534-2553
Energy harvesting technique for efficient wireless cognitive sensor networks based on SWIPT game theory Fadhil Mukhlif, Kamarul Ariffin Bin Noordin, Omar B. Abdulghafoor p. 2709-2734
Security performance analysis of SIMO relay systems over composite fading channels Jiangfeng Sun, Hongxia Bie, Xingwang Li p. 2649-2669
Redundant rule detection for software-defined networking Jian Su, Ruoyu Xu, ShiMing Yu, BaoWei Wang, Jiuru Wang p. 2735-2751
A GQM approach to evaluation of the quality of smartthings applications using static analysis Byeong-Mo Chang, Janine Cassandra Son, Kwanghoon Choi p. 2354-2376
A smart framework for mobile botnet detection using static analysis Shahid Anwar, Mohamad Fadli Zolkipli, Vitaliy Mezhuyev, Zakira Inayat p. 2591-2611

참고문헌 (39건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 네이버 미소장
2 C. Glackin, G. Chollet, N. Dugan, N. Cannings, J. Wall, S. Tahir and M. Rajarajan, “Privacy preserving encrypted phonetic search of speech data,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 6414-6418, March 5-7, 2017. 미소장
3 H. Wang, L. Zhou, W. Zhang and H. Liu, “Watermarking-based perceptual hashing search over encrypted speech,” in Proc. of Int. Workshop on Digital Watermarking. Springer, Berlin, Heidelberg, pp. 423-434, July 9, 2014. 미소장
4 H. X. Wang and G. Y. Hao, “Encryption speech perceptual hashing algorithm and retrieval scheme based on time and frequency domain change characteristics,” China Patent CN104835499A, Aug 12, 2015. 미소장
5 H. Zhao and S. He, “A retrieval algorithm for encrypted speech based on perceptual hashing,” in Proc. of 12th Int. Conf. on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp. 1840-1845, Aug 13-15, 2016. 미소장
6 S. He and H. Zhao, “A retrieval algorithm of encrypted speech based on syllable-level perceptual hashing,” Computer Science & Information Systems, vol. 14, no. 3, pp. 703-718, 2017. 미소장
7 A retrieval algorithm of encrypted speech based on short-term cross-correlation and perceptual hashing 네이버 미소장
8 Deep CNN based binary hash video representations for face retrieval 네이버 미소장
9 Supervised deep hashing for scalable face image retrieval 네이버 미소장
10 Global and local semantics-preserving based deep hashing for cross-modal retrieval 네이버 미소장
11 Triplet-Based Deep Hashing Network for Cross-Modal Retrieval 네이버 미소장
12 Y. Cao, M. Long, B. Liu and J. Wang, “Deep cauchy hashing for hamming space retrieval,” in Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, pp. 1229-1237, 2018. 미소장
13 Deep Self-Taught Hashing for Image Retrieval 네이버 미소장
14 Discriminative Deep Quantization Hashing for Face Image Retrieval 네이버 미소장
15 A privacy-preserving image retrieval scheme based secure kNN, DNA coding and deep hashing 네이버 미소장
16 I. Song, J. Chung, T. Kim and Y. Bengio, “Dynamic Frame Skipping for Fast Speech Recognition in Recurrent Neural Network Based Acoustic Models,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 4984-4988, April 15-20, 2018. 미소장
17 M. Fujimoto and H. Kawai, “Comparative Evaluations of Various Factored Deep Convolutional Rnn Architectures for Noise Robust Speech Recognition,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 4829-4833, April 15-20, 2018. 미소장
18 Parsimonious memory unit for recurrent neural networks with application to natural language processing 네이버 미소장
19 Putting hands to rest: efficient deep CNN-RNN architecture for chemical named entity recognition with no hand-crafted rules 네이버 미소장
20 Y. Xu, Q. Kong, W. Wang and M. D. Plumbley, “Large-scale weakly supervised audio classification using gated convolutional neural network,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 121-125, April 15-20, 2018. 미소장
21 J. Sang, S. Park and J. Lee, “Convolutional Recurrent Neural Networks for Urban Sound Classification Using Raw Waveforms,” in Proc. of 26th European Signal Processing Conference (EUSIPCO), pp. 2444-2448, Sept. 3-7, 2018. 미소장
22 R. Pradeep and K. S. Rao, “Incorporation of Manner of Articulation Constraint in LSTM for Speech Recognition,” Circuits, Systems, and Signal Processing, vol. 38, no. 8, pp. 3482-3500, August, 2019. 미소장
23 S. Ghorbani, A. E. Bulut and J. H. L. Hansen, “Advancing Multi-Accented Lstm-CTC Speech Recognition Using a Domain Specific Student-Teacher Learning Paradigm,” in Proc. of IEEE Spoken Language Technology Workshop (SLT), pp. 29-35, Dec. 18-21, 2018. 미소장
24 Long short-term memory with attention and multitask learning for distant speech recognition 네이버 미소장
25 Attention-Based Dense LSTM for Speech Emotion Recognition 네이버 미소장
26 F. Tao and G. Liu, “Advanced LSTM: A study about better time dependency modeling in emotion recognition,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 2906-2910, April 15-20, 2018. 미소장
27 G. Ramet, P. N. Garner, M. Baeriswyl and A. Lazaridis, “Context-Aware Attention Mechanism for Speech Emotion Recognition.” in Proc. of IEEE Spoken Language Technology Workshop (SLT), pp. 126-131, Dec. 18-21, 2018. 미소장
28 C. Etienne, G. Fidanza, A. Petrovskii, L. Devillers and B. Schmauch, “Cnn+ lstm architecture for speech emotion recognition with data augmentation,” in Proc. of Workshop on Speech, Music and Mind 2018, 21-25, 2018. 미소장
29 S. Jung, J. Park and S. Lee, “Polyphonic Sound Event Detection Using Convolutional Bidirectional Lstm and Synthetic Data-based Transfer Learning,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 885-889, May 12-17, 2019. 미소장
30 T. Matsuyoshi, T. Komatsu, R. Kondo, T. Yamada and S. Makino, “Weakly labeled learning using BLSTM-CTC for sound event detection,” in Proc. of Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 1918-1923, Nov. 12-15, 2018. 미소장
31 J. Liu, Y. Yin, H. Jiang, H. Kan, Z. Zhang, P. Chen, B. Zhu and Z. Wang, “Bowel Sound Detection Based on MFCC Feature and LSTM,” in Proc. of IEEE Biomedical Circuits and Systems (BioCAS), pp. 1-4, Oct. 17-19, 2018. 미소장
32 B. Elizalde, S. Zarar and B. Raj, “Cross Modal Audio Search and Retrieval with Joint Embeddings Based on Text and Audio,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 4095-4099, May 12-17, 2019. 미소장
33 S. B. Davis and P. Mermelstein, “Evaluation of acoustic parameters for monosyllabic word recognition in continuously spoken sentences,” The Journal of the Acoustical Society of America, vol.64, pp. s180-s181, 1978. 미소장
34 Y. Xu, Q. Kong, W. Wang and M. D. Plumbley, “Large-scale weakly supervised audio classification using gated convolutional neural network,” in Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 121-125, April 15-20, 2018. 미소장
35 Long short-term memory. 네이버 미소장
36 New dynamics coined in a 4-D quadratic autonomous hyper-chaotic system 네이버 미소장
37 B. McFee, C. Raffel, D. Liang, D. P. Ellis, M. McVicar, E. Battenberg and O. Nieto, “librosa: Audio and music signal analysis in python,” in Proc. of the 14th python in science conference, pp. 18-24, 2015. 미소장
38 D. Wang and X. Zhang, “Thchs-30: A free Chinese speech corpus,” arXiv preprint arXiv:1512.01882, 2015. 미소장
39 ITU-T Recommendation P.862, Perceptual Evaluation of Speech Quality (PESQ): An Objective Method for End-to-End Speech Quality Assessment of Narrow-band Telephone Networks and Speech Codecs, ITU-T, Jan. 2002. 미소장

추천서가 (다양한 추천 자료를 만나보세요)

권호기사보기

권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 기사목차