Security Analysis of Speech Perceptual Hashing Authentication Algorithm

Zhang Qiu-yu,Ren Zhan-wei,Xing Peng-fei,Huang Yi-bo,Yu Shuang 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.1

Speech perceptual hashing authentication algorithm is an efficient method for content integrity authentication and identity authentication. But the algorithm becomes transparent under the principle of Kerckhoffs which makes the algorithm unsafe. In this paper, the algorithm is encrypted under the principle of Kerckhoffs to protect the security of the algorithm. Then the specific link that won’t affect the performance of the algorithm is identified through the experiments. Next, this paper analyzes the security of the encrypted algorithm based on the concept of Shannon unicity distance. The unicity distance is figured out finally based on the experiments. That is to say, the algorithm loses its security even though the algorithm has been encrypted. Under this circumstances, the most important thing is to continue keeping the safety of the algorithm. Therefore, this paper proposed an efficient random secret key method to guarantee the safety of the algorithm after the unicity distance is figured out.

Security Authentication Method of Speech Perceptual Hashing Based on Fuzzy Commitment Scheme

Zhang Qiu-yu,Ren Zhan-wei,Huang Yi-bo,Yu Shuang,Hu Wen-jin 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.1

Existing speech perceptual hashing authentication algorithms generally encrypt the perceptual hash value to protect the security of the algorithms. But under the principle of Kerckhoffs, the algorithm becomes transparent and fragile. And it can be seen that the secret key may be estimated when the number of times that reuses the secret key reache to a limit through the safety analysis of Shannon unicity distance. To solve these problems, we present a novel security authentication scheme of speech perceptual hashing based on the fuzzy commitment scheme (FCS). Firstly, in sender, the randomly selected BCH code word and the extracted perceptual hash value are sent to the Cmt() function to calculate and the final secure perceptual hash value (h(c),) can be obtained. Secondly, in receiver, the perceptual hash value is calculated again from the received speech information and then the calculated perceptual hash value with the received information  (commitment) are sent to the Decmt() function to calculate to get the h(c′). Finally, the h(c) and h(c′) are matched. The experimental results show that the proposed scheme effectively avoids the probability that an attacker obtains the plaintext/ciphertext pairs without affecting the performance of original algorithm, and at the same time it ensures the security of perceptual hashing algorithm.

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 ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.6

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.

A Dynamic Gesture Trajectory Recognition Based on Key Frame Extraction and HMM

Zhang Qiu-yu,Lv Lu,Zhang Mo-yi,Duan Hong-xiang,Lu Jun-chi 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.6

Aiming at changing high computational complexity, underdeveloped real time, low recognition rate of dynamic gesture recognition algorithms, this paper present a real-time dynamic gesture trajectory recognition method based on key frame extraction and HMM. Key frames are selected without keeping track of all the details of one dynamic gesture, which is based on difference degree between frames. The trajectory data stream, sorted by the time-warping algorithm, is used to construct the Hidden Markov Method model of dynamic gesture. Finally, optimal transition probabilities are employed to implement dynamic gesture recognition. The result of this experiment implies that this method has high robustness and real time. The average recognition rate of dynamic gesture (0~9) is up to 87.67%, and average time efficiency is 0.46s.

Dynamic Hand Gesture Segmentation Method Based on Improved Kalman Filter and Weighted Skin-Color Model

Zhang Qiu-yu,Lu Jun-chi,Wei Hui-yi,Zhang Mo-yi,Duan Hong-xiang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6

In order to improve the problems of segmentation accuracy and real-time existing in dynamic hand gesture under complex backgrounds, this paper presents a kind of dynamic hand gesture segmentation method based on improved Kalman filter and weighted skin-color model. Firstly, improved Kalman filter is utilized to process hand gesture image of hand gesture video sequences and get rough hand gesture results. Secondly, weighted skin-color model is applied to process rough results of hand gesture segmentation and segment hand gesture. Finally, morphological method is utilized to deal with gesture segmentation result, getting rid of the holes in the hand gesture’s binary image to realize the segmentation of dynamic hand gesture. Experiments show that the proposed method can segment hand gesture from dynamic hand gesture video sequences with complex backgrounds effectively. And the accuracy of hand gesture segmentation is high.

Dynamic Hand Gesture Trajectory Recognition Based on Block Feature and Skin-Color Clustering

Zhang Qiu-yu,Lv Lu,Lu Jun-chi,Zhang Mo-yi,Duan Hong-xiang 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.12

In recent years, dynamic hand gesture recognition has been a research hotspot of human-computer interaction. Since most existing algorithms contain problems with high computational complexity, poor real-time performance and low recognition rate, which cannot satisfy the need of many practical applications. Moreover, key frames obtained by inter-frame difference degree algorithm contain less information, which leads to less identified species and lower recognition rate. To solve these problems, we present a dynamic hand gesture trajectory recognition method based on the theory of block feature to extract key frames and the skin-color clustering’s hand gesture segmentation. Firstly, this method extracts block feature of degree of difference between frames in hand gesture sequence to select key frames accurately. Secondly, the method based on skin-color clustering is applied to obtain the area of hand gesture after segmenting hand gestures from images. Finally, hidden Markov model (HMM), in which the angle data of hand gesture trajectories are input, is used for modeling and identifying dynamic hand gestures. Experimental results show that the method of key-frame extraction is used to obtain information of dynamic hand gestures accurately, which would improve the recognition rate of dynamic hand gesture recognition and, at the same time, can guarantee the real-time of hand gesture recognition system. The average recognition rate is up to 86.67%, and the average time efficiency is 0.39s.

Audio Fingerprint Retrieval Method Based on Feature Dimension Reduction and Feature Combination

( Qiu-yu Zhang ),( Fu-jiu Xu ),( Jian Bai ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.2

In order to solve the problems of the existing audio fingerprint method when extracting audio fingerprints from long speech segments, such as too large fingerprint dimension, poor robustness, and low retrieval accuracy and efficiency, a robust audio fingerprint retrieval method based on feature dimension reduction and feature combination is proposed. Firstly, the Mel-frequency cepstral coefficient (MFCC) and linear prediction cepstrum coefficient (LPCC) of the original speech are extracted respectively, and the MFCC feature matrix and LPCC feature matrix are combined. Secondly, the feature dimension reduction method based on information entropy is used for column dimension reduction, and the feature matrix after dimension reduction is used for row dimension reduction based on energy feature dimension reduction method. Finally, the audio fingerprint is constructed by using the feature combination matrix after dimension reduction. When speech’s user retrieval, the normalized Hamming distance algorithm is used for matching retrieval. Experiment results show that the proposed method has smaller audio fingerprint dimension and better robustness for long speech segments, and has higher retrieval efficiency while maintaining a higher recall rate and precision rate.

Hand Gesture Segmentation Method Based on YCbCr Color Space and K-Means Clustering

Zhang Qiu-yu,Lu Jun-chi,Zhang Mo-yi,Duan Hong-xiang,Lv Lu 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.5

Aiming at the problems that current skin-color detection segmentation technologies have unsatisfied segmentation results under conditions of complex illumination or backgrounds, we present a new method based on YCbCr color space and K-means clustering algorithm for segmentation hand gesture. Firstly, image in RGB color space is converted to YCbCr color space; and then YCbCr color space of image is divided into luminance Y and chrominance Cb and Cr. Lastly, the binary image is achieved by clustering values of chrominance using k-means clustering algorithm, and hand gesture segmentation is completed by conducting morphological process of binary image obtained. The experimental results illustrate that the proposed method can segment hand gestures from complex backgrounds and obtain segmentation results. The phenomena of similar skin color interference and skin color overlapping are solved with this method effectively. In addition, it is robust to illumination condition.

Risk Factors for Cervical Cancer in Rural Areas of Wuhan China: a Matched Case-control Study

Zhang, Bin,Zhou, Ai-Fen,Zhu, Chang-Cai,Zhang, Ling,Xiang, Bing,Chen, Zhong,Hu, Rong-Hua,Zhang, Ya-Qi,Qiu, Lin,Zhang, Yi-Ming,Xiong, Chao-Du,Du, Yu-Kai,Shi, Yu-Qin Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.12

Cervical cancer is a serious public health problem in developing countries. We investigated possible risk factors for cervical cancer in rural areas of Wuhan China using a matched case-control study with 33 women diagnosed with cervical cancer and 132 healthy women selected from the same area as matched controls. A questionnaire, which included questions about general demography conditions, environmental and genetic factors, the first sexual intercourse, first marriage age, age at first pregnancy, pregnancy first child's age, female personal health history, social psychological factors, dietary habits, smoking and alcohol status and other living habits was presented to all participants. At the same time, HPV infection of every participant was examined in laboratory testing. Results showed HPV infection (P<0.000, OR=23.4) and pregnancy first child's age (P<0.000, OR=13.1) to be risk factors for cervical cancer. Menopause (P=0.003, OR=0.073) was a protective factor against cervical cancer. However, there was no indication of associations of environmental (drinking water, insecticide, disinfectant) genetic (cancer family history), or life-style factors (smoking status, alcohol status, physical training, sleep quality), including dietary habits (intake of fruit and vegetable, meat, fried food, bean products and pickled food) or social psychological factors with cervical cancer. The results suggest that the risk of cervical cancer in Chinese rural women may be associated with HPV infection, menopause and the pregnancy first child's age.

Comparison of Liver Transplantation and Liver Resection for Hepatocellular Carcinoma Patients with Portal Vein Tumor Thrombus Type I and Type II

Jia-Yu Lv,Ning-Ning Zhang,Ya-Wei Du,Ying Wu,Tian-Qiang Song,Ya-Min Zhang,Yan Qu,Yu-Xin Liu,Jie Gu,Ze-Yu Wang,Yi-Bo Qiu,Bing Yang,Da-Zhi Tian,Qing-Jun Guo,Li Zhang,Ji-San Sun,Yan Xie,Zheng-Lu Wang,Xin 연세대학교의과대학 2021 Yonsei medical journal Vol.62 No.1

Purpose: The aim of this study was to compare the efficacy of liver transplantation (LT) and liver resection (LR) for hepatocellularcarcinoma (HCC) patients with portal vein tumor thrombus (PVTT) and to investigate risk factors affecting prognosis. Materials and Methods: A total of 94 HCC patients with PVTT type I (segmental PVTT) and PVTT type II (lobar PVTT) were involvedand divided into LR (n=47) and LT groups (n=47). Recurrence-free survival (RFS) and overall survival (OS) were comparedbefore and after inverse probability of treatment weighting (IPTW). Prognostic factors for RFS and OS were explored. Results: Two treatment groups were well-balanced using IPTW. In the entire cohort, LT provided a better prognosis than LR. Among patients with PVTT type I, RFS was better with LT (p=0.039); OS was not different significantly between LT and LR(p=0.093). In subgroup analysis of PVTT type I patients with α-fetoprotein (AFP) levels >200 ng/mL, LT elicited significantly longermedian RFS (18.0 months vs. 2.1 months, p=0.022) and relatively longer median OS time (23.6 months vs. 9.8 months, p=0.065). Among patients with PVTT type II, no significant differences in RFS and OS were found between LT and LR (p=0.115 and 0.335,respectively). Multivariate analyses showed treatment allocation (LR), tumor size (>5 cm), AFP and aspartate aminotransferase(AST) levels to be risk factors of RFS and treatment allocation (LR), AFP and AST as risk factors for OS. Conclusion: LT appeared to afford a better prognosis for HCC with PVTT type I than LR, especially in patients with AFP levels>200 ng/mL.