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

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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Koebe Type Theorems and Pre-Schwarzian of Harmonic K-quasiconformal Mappings,and Their Applications

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Acta Mathematica Sinica,English Series 2022年第11期38卷 1965-1980页

作者： Shao Lin CHEN Saminathan PONNUSAMY College of Mathematics and Statistics Hengyang Normal UniversityHengyang 421002P.R.China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang 421002P.R.China Department of Mathematics Indian Institute of Technology MadrasChennai-600036India

In this article,we first establish an asymptotically sharp Koebe type covering theorem for harmonic K-quasiconformal *** we use it to obtain an asymptotically Koebe type distortion theorem,a coefficients estimate,a Lipschitz characteristic and a linear measure distortion theorem of harmonic K-quasiconformal *** last,we give some characterizations of the radial John disks with the help of pre-Schwarzian of harmonic mappings.

关键词： Harmonic K-quasiconformal mapping Koebe type covering theorem Koebe type distortion theorem Radial John disk

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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 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 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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Two Physics-Based Schwarz Preconditioners for Three-Temperature Radiation Diffusion Equations in High Dimensions

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Communications in Computational Physics 2022年第8期32卷 829-849页

作者： Xiaoqiang Yue Jianmeng He Xiaowen Xu Shi Shu Libo Wang National Center for Applied Mathematics in Hunan Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationHunan Key Laboratory for Computation and Simulation in Science and EngineeringXiangtan UniversityXiangtan 411105P.R.China Laboratory of Computational Physics Institute of Applied Physics and ComputationalMathematicsBeijing 100094P.R.China College of Information Science and Technology JinanUniversityGuangzhou 510632P.R.China

We concentrate on the parallel,fully coupled and fully implicit solution of the sequence of 3-by-3 block-structured linear systems arising from the symmetrypreserving finite volume element discretization of the unsteady three-temperature radiation diffusion equations in high *** this article,motivated by[***,***,***,SIAM *** ***.33(2012)653–680]and[***,***,***,***.442(2021)110513],we aim to develop the additive and multiplicative Schwarz preconditioners subdividing the physical quantities rather than the underlying domain,and consider their sequential and parallel implementations using a simplified explicit decoupling factor approximation and algebraic multigrid subsolves to address such linear ***,computational efficiencies and parallel scalabilities of the proposed approaches are numerically tested in a number of representative real-world capsule implosion benchmarks.

关键词： Radiation diffusion equations Schwarz methods algebraic multigrid parallel and distributed computing

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Federated Multitask Learning for HyperFace

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第5期3卷 788-797页

作者： Zhang, Chen Bai, Hang Zhang, Yonggang Niu, Xinyi Yu, Bin Gao, Yuan Xie, Yu Xidian University School of Computer Science and Technology Xi'an710071 China Shaanxi Province Science and Technology Resources Coordination Center Xi'an710071 China Xidian University Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education Xi'an710071 China Shanxi University Key Laboratory of Computational Intelligence and Chinese Information Processing Ministry of Education Taiyuan030006 China

Multitask learning (MTL) is a promising field in machine learning owing to its capability to improve the generalization performance of all tasks by sharing knowledge among the related tasks. MTL has attracted a large amount of attention in the multitask-related community. In recent years, with the rapid development of distributed machine learning, MTL in a distributed environment becomes a hot research topic. Although MTL can reap great fruit in a distributed environment, the sensitive information, such as photos and voice recordings of the owner, in distributed data may be leaked during training. Consequently, in the distributed settings, one prominent challenge of MTL is to prevent the disclosure of sensitive private data. In this article, we propose a novel approach, federated multitask learning (FMTL), which applies federated learning to MTL in a distributed environment in order to protect the MTL model from being leaked and to better optimize the utility of the MTL model. In FMTL, all the participants independently train their local models on their own dataset in parallel and only transmit their model updates to the central server for aggregation at every epoch. As a result, their learning accuracy is enhanced beyond what is achieved only on their own training data. In this manner, it can achieve the best tradeoff between the utility and privacy: participants not only preserve the privacy of their own data, but also benefit from the models of other participants. The experimental results on annotated facial landmarks in the wild (AFLW) and annotated faces in the wild (AFW) benchmark datasets verify the effectiveness of our framework. © 2020 IEEE.

关键词： Linearization

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Cross-Modality Perturbation Synergy Attack for Person Re-identification 38

Cross-Modality Perturbation Synergy Attack for Person Re-ide...

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38th Conference on Neural information processing Systems, NeurIPS 2024

作者： Gong, Yunpeng Zhong, Zhun Qu, Yansong Luo, Zhiming Ji, Rongrong Jiang, Min School of Informatics Xiamen University China School of Computer Science and Information Engineering Hefei University of Technology China The Department of Artificial Intelligence Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China School of Informatics Key Laboratory of Digital Protection and Intelligent Processing of Intangible CulturalHeritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University Fujian Xiamen361005 China

In recent years, there has been significant research focusing on addressing security concerns in single-modal person re-identification (ReID) systems that are based on RGB images. However, the safety of cross-modality scenarios, which are more commonly encountered in practical applications involving images captured by infrared cameras, has not received adequate attention. The main challenge in cross-modality ReID lies in effectively dealing with visual differences between different modalities. For instance, infrared images are typically grayscale, unlike visible images that contain color information. Existing attack methods have primarily focused on the characteristics of the visible image modality, overlooking the features of other modalities and the variations in data distribution among different modalities. This oversight can potentially undermine the effectiveness of these methods in image retrieval across diverse modalities. This study represents the first exploration into the security of cross-modality ReID models and proposes a universal perturbation attack specifically designed for cross-modality ReID. This attack optimizes perturbations by leveraging gradients from diverse modality data, thereby disrupting the discriminator and reinforcing the differences between modalities. We conducted experiments on three widely used cross-modality datasets, namely RegDB, SYSU, and LLCM. The results not only demonstrate the effectiveness of our method but also provide insights for future improvements in the robustness of cross-modality ReID systems. © 2024 Neural information processing systems foundation. All rights reserved.

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Object Detection Algorithm Based on Coordinate Attention and Context Feature Enhancement 22

Object Detection Algorithm Based on Coordinate Attention and...

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Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition

作者： Lingzhi Liu Baohua Qiang Yuanchun Wang Xianyi Yang Jubo Tian Shihao Zhang Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology China Hebei Key Laboratory of Intelligent Information Perception and Processing The 54th Research Institute of CETC China

ISBN: (纸本)9781450397056

In recent years, object detection has been widely used in various fields such as face detection, remote sensing image detection and pedestrian detection. Due to the complex environment in the actual scene, we need to fully obtain the feature information in the image to improve the accuracy of object detection. This paper proposes an object detection algorithm based on coordinate attention and contextual feature enhancement. We design a multi-scale attention feature pyramid network, which first uses multi-branch atrous convolution to capture multi-scale context information, and then fuses the coordinate attention mechanism to embed location information into channel attention, and finally uses a bidirectional feature pyramid structure to effectively fuse high-level features and low-level features. We also adopt the GIoU loss function to further improve the accuracy of object detection. The experimental results show that the proposed method has certain advantages compared with other detection algorithms in the PASCAL VOC datasets.

关键词： Feature pyramid network Object detection Coordinate attention Atrous convolution

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