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International Conference on Computer Supported Cooperative Work in Design

作者： Hua Ma Peiji Huang Xi Luo Qiong Huang Xiangru Fu Wensheng Tang College of Information Science and Engineering Hunan Normal University Changsha China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Teaching early warning is of great significance for avoiding teaching risks and continuously improving teaching quality. However, none of existing approaches assess the degree of course goals attainment and teacher's teaching quality from the perspective of cognitive diagnosis. This poses a challenge in providing accurate teaching early warning. This paper proposed an early warning approach for teachers based on cognitive diagnosis and long short-term memory (LSTM). First, this approach accurately evaluates students' cognitive status on knowledge concepts using a cognitive diagnosis model to assess their knowledge understanding degree and knowledge application ability. Second, the cognitive status on knowledge concepts is utilized to assess students' attainment degree of course goals and teachers' teaching quality. Third, the teachers' teaching quality is predicted in the future by using the LSTM network to mine students' learning process data, Finally, an accurate teaching early warning is provided to teachers based on a four-level early warning evaluation rule. In experiments, the real datasets are used and the results reveal that the proposed approach can accurately diagnose students' cognitive status and effectively predict teachers' teaching quality. This approach can provide an accurate teaching early warning service for teachers.

关键词： Accuracy Fluctuations Federated learning Computational modeling Education Predictive models Data mining

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A New Image Encryption Strategy Based on Arnold Transformation and Logistic Map 11th

A New Image Encryption Strategy Based on Arnold Transformati...

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11th International Conference on Computer Engineering and Networks, CENet2021

作者： Sun, Xiyu Chen, Zhong College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9789811665530

Aiming at the problem of digital image encryption, an image encryption algorithm is proposed. The algorithm is divided into preparation stage and permutation diffusion stage. In the preparation stage, Arnold algorithm is improved and combined with Logistic chaotic map to generate the necessary sequence for the next stage. In the permutation diffusion stage, the final encrypted image is obtained by permutation, positive XOR operation, shift operation, S-box substitution and reverse XOR operation. The experimental results show that the algorithm can effectively resist the common attacks. For the 128 × 128 Lena gray image, the resistance performance number of pixel change rate (NPCR) is 99.6090, unified average changing intensity (UACI) is 33.4316. In addition, the time consumption of the algorithm is about 0.0055 s, and the experiments show that the algorithm has high security and real-time performance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Chaotic systems

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A Stronger Leakage Model Based on Conditional Generative Adversarial Networks for Correlation Power Analysis

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International Journal of Circuit Theory and Applications 2025年第0期

作者： Tang, Cheng Li, Lang Ou, Yu College of Computer Science and Technology Hengyang Normal University Hengyang China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal University Hengyang China

Deep learning-based side-channel attacks (DL-SCA) have attracted widespread attention in recent years, and most of the researchers are devoted to finding the optimal DL-SCA method. At the same time, traditional SCA methods have lost their luster. However, traditional attacks still have certain advantages. Compared with the DL-SCA method, they do not require cumbersome engineering of tuning DL models and hyperparameters, making them easier to implement. Correlation power analysis (CPA), as a traditional SCA method, is still widely used in various analysis scenarios and plays an important role. In CPA, the leakage model is the key to simulating the power consumption, and it decides the attack efficiency. However, the existing leakage models are designed based on theory but ignore the actual attack scene. We found that conditional generative adversarial networks (CGAN) can ideally learn the target device's leakage characteristics and real power consumption. We let CGAN pre-learn the leakage of the target device, and then make the generator as the leakage model (Formula presented.). The (Formula presented.) leakage model can characterize the leakages of the device and consider the presence of noise in the actual scenario. It can map the power consumption more realistically and accurately, which can lead to a more powerful CPA attack. In this work, three kinds of (Formula presented.) leakage models ((Formula presented.) 1, (Formula presented.) 2, and (Formula presented.) 3 leakage models) corresponding to the labels least significant bit (LSB), hamming weight (HW), and identity (ID) of CGAN are discussed. The experimental results show that the (Formula presented.) 3 leakage model has better attack performance. Compared with the ordinary HW leakage model, the number of traces needed to recover the key on the ASCAD and SAKURA-AES datasets reduced by about 38.9% and 85.9%, respectively. © 2025 John Wiley & Sons Ltd.

关键词： Generative adversarial networks

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A new S-box construction method meeting strict avalanche criterion

A new S-box construction method meeting strict avalanche cri...

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作者： Li, Lang Liu, Jinggen Guo, Ying Liu, Botao College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

S-box is the main security component in lightweight block ciphers. Finding new algorithms and technical applications to generate S-box is still a current research topic. We proposed an S-box construction method that satisfies the strict avalanche criterion. It includes a nonlinear layer and a diffusion layer. These layers enable the constructed S-box to maintain good nonlinearity, differential uniformity, strict avalanche criterion, and a high number of algebraic terms. Secondly, we listed 20 existing classic 4 × 4 S-boxes and tested their cryptographic properties such as nonlinearity, difference uniformity, strict avalanche criterion, algebraic degree, algebraic item number, and fixed point. At the same time, the test results are compared with the proposed S-box. The results show that these cryptographic properties of our proposed S-box are superior to other S-boxes. In addition, we evaluated the proposed S-box hardware implementation overhead. To evaluate our S-box more objectively, we tested the above 20 S-boxes hardware implementation overhead under the same conditions, and the results show that the S-box we constructed achieved a good balance between cryptographic properties and hardware overhead. © 2022 Elsevier Ltd

关键词： Algebra

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A New Encryption Scheme Based on RSA Encryption Algorithm and Chen Chaotic System 12th

A New Encryption Scheme Based on RSA Encryption Algorithm an...

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12th International Conference on Computer Engineering and Networks, CENet 2022

作者： He, Chenchen Chen, Zhong College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9789811969003

Nowadays the security of images is obviously more important. Some scholars have applied Rivest-Shamir-Adleman (RSA) algorithm and Chen chaotic system to image encryption. However, the application of the two methods in image encryption can still be explored. In this paper, it proposes an encryption scheme which uses asymmetric cipher RSA encryption algorithm and Chen chaotic system to scramble and diffuse the image. In this encryption scheme, firstly, it applies the RSA algorithm to obtain the public key and uses the specified formula to calculate the initial value of the Chen chaotic system. Secondly, the four chaotic sequences generated by Chen chaotic system are applied to the scrambling stage and the diffusion stage of the image process respectively. In the scrambling phase, it uses Arnold scrambling. It performs forward XOR diffusion and then performs reverse XOR diffusion in the diffusion stage. Finally, the encryption process is all completed and the encrypted image is obtained. Moreover, after appropriate experiments, the encryption algorithm is proved to have a good guarantee for the security of the image. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Diffusion

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Hyperchaotic Image Encryption Algorithm Based on BD-Zigzag Transformation and DNA Coding 12th

Hyperchaotic Image Encryption Algorithm Based on BD-Zigzag T...

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12th International Conference on Computer Engineering and Networks, CENet 2022

作者： Wang, Lujie Chen, Zhong College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9789811969003

For the features of Zigzag transformation, a Bidirectional Deformed Zigzag (BD-Zigzag) transformation is proposed in this paper, which starts from both sides of the diagonal and crosses in both directions. This method is more complex than the traditional Zigzag transformation method and has better dislocation effect. Then, a Hyperchaotic image encryption algorithm based on BD-Zigzag transformation and DNA coding is proposed. First, the images are processed with multiple rounds of permutations using the BD-Zigzag transformation. Second, a 4D-hyperchaotic Lorenz system is used to produce random numbers to permute the images at the bit level. Finally, DNA encoding is used to diffuse the pixels in the image. The experimental simulations and performance analysis data can prove that the encryption algorithm has high-level security capability. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： DNA

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Modality Unified Attack for Omni-Modality Person Re-Identification

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IEEE Transactions on information Forensics and Security 2025年

作者： Bian, Yuan Liu, Min Yi, Yunqi Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning based person re-identification (re-id) models have been widely employed in surveillance systems. Recent studies have demonstrated that black-box single-modality and cross-modality re-id models are vulnerable to adversarial examples (AEs), leaving the robustness of multi-modality re-id models unexplored. Due to the lack of knowledge about the specific type of model deployed in the target black-box surveillance system, we aim to generate modality unified AEs for omni-modality (single-, cross- and multi-modality) re-id models. Specifically, we propose a novel Modality Unified Attack method to train modality-specific adversarial generators to generate AEs that effectively attack different omni-modality models. A multi-modality model is adopted as the surrogate model, wherein the features of each modality are perturbed by metric disruption loss before fusion. To collapse the common features of omnimodality models, Cross Modality Simulated Disruption approach is introduced to mimic the cross-modality feature embeddings by intentionally feeding images to non-corresponding modality-specific subnetworks of the surrogate model. Moreover, Multi Modality Collaborative Disruption strategy is devised to facilitate the attacker to comprehensively corrupt the informative content of person images by leveraging a multi modality feature collaborative metric disruption loss. Extensive experiments show that our MUA method can effectively attack the omni-modality re-id models, achieving 55.9%, 24.4%, 49.0% and 62.7% mean mAP Drop Rate, respectively. © 2005-2012 IEEE.

关键词： Modality unified attack Multi Modality Collaborative Disruption Omni-Modality re-id

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Learning to Learn Transferable Generative Attack for Person Re-Identification

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IEEE Transactions on Image processing 2025年 PP卷 PP页

作者： Bian, Yuan Liu, Min Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning-based person re-identification (reid) models are widely employed in surveillance systems and inevitably inherit the vulnerability of deep networks to adversarial attacks. Existing attacks merely consider cross-dataset and cross-model transferability, ignoring the cross-test capability to perturb models trained in different domains. To powerfully examine the robustness of real-world re-id models, the Meta Transferable Generative Attack (MTGA) method is proposed, which adopts meta-learning optimization to promote the generative attacker producing highly transferable adversarial examples by learning comprehensively simulated transfer-based crossmodel&dataset&test black-box meta attack tasks. Specifically, cross-model&dataset black-box attack tasks are first mimicked by selecting different re-id models and datasets for meta-train and meta-test attack processes. As different models may focus on different feature regions, the Perturbation Random Erasing module is further devised to prevent the attacker from learning to only corrupt model-specific features. To boost the attacker learning to possess cross-test transferability, the Normalization Mix strategy is introduced to imitate diverse feature embedding spaces by mixing multi-domain statistics of target models. Extensive experiments show the superiority of MTGA, especially in cross-model&dataset and cross-model&dataset&test attacks, our MTGA outperforms the SOTA methods by 20.0% and 11.3% on mean mAP drop rate, respectively. © 1992-2012 IEEE.

关键词： Generative adversarial networks

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Congruences for modular forms and applications to crank functions

arXiv

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arXiv 2022年

作者： Zhang, Hao Zhang, Helen W.J. School of Mathematics Hunan University Changsha410082 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Applied Mathematics Changsha410082 China

In this paper, motivated by the work of Mahlburg, we find congruences for a large class of modular forms. Moreover, we generalize the generating function of the Andrews-Garvan-Dyson crank on partition and establish several new infinite families of congruences. In this framework, we showed that both the birank of an ordered pair of partitions introduced by Hammond and Lewis, and k-crank of k-colored partition introduced by Fu and Tang process the same as the partition function and *** Codes 05A17, 11P83 © 2022, CC BY.

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HIGHER ORDER ISOMETRIC SHIFT OPERATOR ON THE DE BRANGES-ROVNYAK SPACE

arXiv

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arXiv 2023年

作者： Gu, Caixing Luo, Shuaibing DEPARTMENT OF MATHEMATICS CALIFORNIA POLYTECHNIC STATE UNIVERSITY SAN LUIS OBISPO CA93407 United States SCHOOL OF MATHEMATICS AND HUNAN PROVINCIAL KEY LABORATORY OF INTELLIGENT INFORMATION PROCESSING AND APPLIED MATHEMATICS HUNAN UNIVERSITY Changsha410082 China

The de Branges-Rovnyak space H(b) is generated by a bounded analytic function b in the unit ball of H∞. When b is a nonextreme point, the space H(b) is invariant by the forward shift operator Mz. We show that the H(b) spaces provide model spaces for expansive quasi-analytic 2n-isometric operators T with T∗T − I being rank one. Then we describe the invariant subspaces of the 2n-isometric forward shift operator Mz on H(b). Copyright © 2023, The Authors. All rights reserved.

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