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126 results on '"Hu, Xuexian"'

1. An Efficient Matrix Multiplication with Enhanced Privacy Protection in Cloud Computing and Its Applications

Author

Liu, Chun, Hu, Xuexian, Chen, Xiaofeng, Wei, Jianghong, and Liu, Wenfen

Subjects
Computer Science - Cryptography and Security
Abstract

As one of the most important basic operations, matrix multiplication computation (MMC) has varieties of applications in the scientific and engineering community such as linear regression, k-nearest neighbor classification and biometric identification. However handling these tasks with large-scale datasets will lead to huge computation beyond resource-constrained client s computation power. With the rapid development of cloud computing, outsourcing intensive tasks to cloud server has become a promising method. While the cloud server is generally out of the control of clients, there are still many challenges concerned with the privacy security of clients sensitive data. Motivated by this, Lei et al. presented an efficient encryption scheme based on random permutation to protect the privacy of client s data in outsourcing MMC task. Nevertheless, there exists inherent security flaws in their scheme, revealing the statistic information of zero elements in the original data thus not satisfying the computational indistinguishability (IND-ZEA). Aiming to enhance the security of the outsourcing MMC task, we propose a new encryption scheme based on subtly designed invertible matrix where the additive perturbation is introduced besides the multiplicative perturbation. Furthermore, we show that the proposed encryption scheme can be applied to not only MMC task but also other kinds of outsourced tasks such as linear regression and principal component analysis. Theoretical analyses and experiments indicate that our methods are more secure in terms of data privacy, with comparable performance to the state-of-the-art scheme based on matrix transformation.

Published
2021

3. A Honeywords Generation Method Based on Deep Learning and Rule-Based Password Attack

Author

Yang, Kunyu, Hu, Xuexian, Zhang, Qihui, Wei, Jianghong, Liu, Wenfen, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Shi, Wenbo, editor, Chen, Xiaofeng, editor, and Choo, Kim-Kwang Raymond, editor

Published
2022
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6. Studies of Keyboard Patterns in Passwords: Recognition, Characteristics and Strength Evolution

Author

Yang, Kunyu, Hu, Xuexian, Zhang, Qihui, Wei, Jianghong, Liu, Wenfen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gao, Debin, editor, Li, Qi, editor, Guan, Xiaohong, editor, and Liao, Xiaofeng, editor

Published
2021
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7. Federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain

Author

YANG Ming, HU Xuexian, ZHANG Qihui, WEI Jianghong and LIU Wenfen

Subjects
mobile network, federated learning, blockchain, reputation management, Electronic computers. Computer science, QA75.5-76.95
Abstract

Federated learning is a new distributed machine learning technology, where training tasks are deployed on user side and training model parameters are sent to the server side. In the whole process, participants do not need to share their own data directly, which greatly avoids privacy issues. However, the trust relationship between mobile users in the learning model has not been established in advance, there is hidden safety when users perform cooperative train with each other. In view of the above problems, a federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain was proposed. The scheme allowed the server side to use subjective logic models to evaluate the reputation of participating mobile users and provided them with credible reputation opinions sharing environment and dynamic access strategy interface based on the technique of smart contract of blockchain. Theoretical and experimental analys is results show that the scheme can enable the server side to select reliable users for training. And it can achieve more fair and effective reputation calculations, which improves the accuracy of federated learning.

Published
2021
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9. Forward-Secure Puncturable Identity-Based Encryption for Securing Cloud Emails

Author

Wei, Jianghong, Chen, Xiaofeng, Wang, Jianfeng, Hu, Xuexian, Ma, Jianfeng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sako, Kazue, editor, Schneider, Steve, editor, and Ryan, Peter Y. A., editor

Published
2019
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10. An Effective Approach for Chinese News Headline Classification Based on Multi-representation Mixed Model with Attention and Ensemble Learning

Author

Lu, Zhonglei, Liu, Wenfen, Zhou, Yanfang, Hu, Xuexian, Wang, Binyu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, Xuanjing, editor, Jiang, Jing, editor, Zhao, Dongyan, editor, Feng, Yansong, editor, and Hong, Yu, editor

Published
2018
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13. An Effective Approach of Sentence Compression Based on 'Re-read' Mechanism and Bayesian Combination Model

Author

Lu, Zhonglei, Liu, Wenfen, Zhou, Yanfang, Hu, Xuexian, Wang, Binyu, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, Cheng, Xueqi, editor, Ma, Weiying, editor, Liu, Huan, editor, Shen, Huawei, editor, Feng, Shizheng, editor, and Xie, Xing, editor

Published
2017
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14. Universally Composable Three-Party Password Authenticated Key Exchange

Author

Zhang, Qihui, Hu, Xuexian, Wei, Jianghong, Liu, Wenfen, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sun, Xingming, editor, Chao, Han-Chieh, editor, You, Xingang, editor, and Bertino, Elisa, editor

Published
2017
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16. Security Analysis of EMV Channel Establishment Protocol in An Enhanced Security Model

Author

Guo, Yanfei, Zhang, Zhenfeng, Zhang, Jiang, Hu, Xuexian, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Hui, Lucas C. K., editor, Qing, S. H., editor, Shi, Elaine, editor, and Yiu, S. M., editor

Published
2015
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17. Revocable Threshold Attribute-Based Signature against Signing Key Exposure

Author

Wei, Jianghong, Huang, Xinyi, Hu, Xuexian, Liu, Wenfen, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Lopez, Javier, editor, and Wu, Yongdong, editor

Published
2015
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19. SDIM: A Subtly Designed Invertible Matrix for Enhanced Privacy-Preserving Outsourcing Matrix Multiplication and Related Tasks

Author

Liu, Chun, Hu, Xuexian, Chen, Xiaofeng, Wei, Jianghong, and Liu, Wenfen

Abstract

Matrix multiplication computation (MMC) is a fundamental operation with various applications, including linear regression, k-nearest neighbor classification and biometric identification. However, performing these tasks with large-scale datasets surpasses the computation capabilities of resource-constrained clients. As outsourcing intensive tasks to cloud server has become a promising method, many matrix-transformation-based privacy-protected schemes have been presented for certain outsourcing tasks, such as Lei et al.'s scheme addresses MMC outsourcing, and Zhao et al.'s scheme focuses on matrix determinant computation. Nevertheless, Lei et al.'s scheme exhibits inherent security flaws, leaking statistical information about zero elements in the original data. Additionally, Zhao et al.'s scheme is task-specific, limiting its application to universal scenarios such as MMC, where clients must compute the inverse matrix of the secret key. Therefore, designing an invertible matrix presents a challenge that affects privacy security, efficiency, and universality of matrix-transformation-based privacy-protected outsourcing computing schemes. To address this issue, we propose a subtly designed invertible matrix (SDIM) and a privacy-protected outsourcing MMC scheme based on SDIM, remedying the security flaws of Lei et al.'s scheme. We also propose an optimized matrix-chain multiplication method to ensure high efficiency of the SDIM-based privacy-protected scheme. This optimization also allows SDIM to be universally applied not only to MMC but also to other related outsourced tasks such as linear regression. Theoretical analyses and experiments have demonstrated that our methods provide enhanced data privacy security while maintaining efficiency comparable to the state-of-the-art scheme based on matrix transformation, i.e., achieving a well-balanced trade-off between security, efficiency, and universality.

Published
2024
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24. Efficient Password-Based Authenticated Key Exchange Protocol in the UC Framework

Author

Hu, Xuexian, Liu, Wenfen, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bao, Feng, editor, Yung, Moti, editor, Lin, Dongdai, editor, and Jing, Jiwu, editor

Published
2010
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25. A New Strongly Secure Authenticated Key Exchange Protocol

Author

Cheng, Qingfeng, Ma, Chuangui, Hu, Xuexian, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Park, Jong Hyuk, editor, Chen, Hsiao-Hwa, editor, Atiquzzaman, Mohammed, editor, Lee, Changhoon, editor, Kim, Tai-hoon, editor, and Yeo, Sang-Soo, editor

Published
2009
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27. On the Rate of Coincidence of Two Clock-Controlled Combiners

Author

Hu, Xuexian, Ming, Yongtao, Liu, Wenfen, Li, Shiqu, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lipmaa, Helger, editor, Yung, Moti, editor, and Lin, Dongdai, editor

Published
2006
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42. Identity-based puncturable signature scheme.

Author

YANG Dongmei, CHEN Yue, WEI Jianghong, and HU Xuexian

Abstract

To overcome the shortcomings of available forward-secure identity-based signature (IBS) scheme in terms of actual practicability and secret key update efficiency, the notion of identity-based puncturable signature (IBPS) scheme was proposed based on the idea of puncturable public-key encryption scheme. Specifically, the syntax and security notion of IBPS were given, and then a concrete IBPS scheme was constructed based on Bloom filter. Under the computational Diffie-Hellman assumption, the proposed scheme achieved the existential unforgeability in the random oracle model. The performance analysis and implementation results demonstrate that, compared with traditional forward-secure IBS schemes, the proposed scheme provides more practical fine-grained forward secrecy, and has higher efficiency of secret key update. [ABSTRACT FROM AUTHOR]

Published
2022
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49. RS-HABE: Revocable-Storage and Hierarchical Attribute-Based Access Scheme for Secure Sharing of e-Health Records in Public Cloud

Author

Wei, Jianghong, Chen, Xiaofeng, Huang, Xinyi, Hu, Xuexian, and Susilo, Willy

Abstract

Personal e-health records (EHR) enable medical workers (e.g., doctors and nurses) to conveniently and quickly access each patient’s medical history through the public cloud, which greatly facilitates patients’ visits and makes telemedicine possible. Additionally, since EHR involve patients’ personal privacy information, EHR holders would hesitate to directly outsource their data to cloud servers. A natural and favorite manner of conquering this issue is to encrypt these outsourced EHR such that only authorized medical workers can access them. Specifically, the ciphertext-policy attribute-based encryption (CP-ABE) supports fine-grained access over encrypted data and is considered to be a perfect solution of securely sharing EHR in the public cloud. In this paper, to strengthen the system security and meet the requirement of specific applications, we add functionalities of user revocation, secret key delegation and ciphertext update to the original ABE, and propose a revocable-storage hierarchical attribute-based encryption (RS-HABE) scheme, as the core building of establishing a framework for secure sharing of EHR in public cloud. The proposed RS-HABE scheme features of forward security (a revoked user can no longer access previously encrypted data) and backward security (a revoked user also cannot access subsequently encrypted data) simultaneously, and is proved to be selectively secure under a complexity assumption in bilinear groups, without random oracles. The theoretical analysis indicates that the proposed scheme surpasses existing similar works in terms of functionality and security, at the acceptable cost of computation overhead. Moreover, we implement the proposed scheme and present experiments to demonstrate its practicability.

Published
2021
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