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28th IACR International Conference on Practice and Theory of Public key Cryptography, PKC 2025

作者： An, Zhiyuan Zhang, Fangguo School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Provincial Key Laboratory of Information Security Technology Guangzhou510006 China

ISBN: (纸本)9783031918285

We introduce an enhanced requirement of deniable public key encryption that we call dual-deniability. It asks that a sender who is coerced should be able to produce fake randomness, which can explain the target ciphertext as the encryption of any alternative message under any valid key she/he desires to deny. Compared with the original notion of deniability (Canetti et al. in CRYPTO ’97, hereafter named message-deniability), this term further provides a shield for the anonymity of the receiver against coercion attacks. We first give a formal definition of dual-deniability, along with its weak-mode variant. For conceptual understanding, we then show dual-deniability implies semantic security and anonymity against CPA, separates full robustness, and even contradicts key-less or mixed robustness, while is (constructively) implied by key-deniability and full robustness with a minor assumption for bits encryption. As for the availability of dual-deniability, our main scheme is a generic approach from ciphertext-simulatable PKE, where we devise a subtle multi-encryption schema to hide the true message within random masking ciphertexts under plan-ahead setting. Further, we leverage the weak model to present a more efficient scheme having negligible detection probability and constant ciphertext size. Besides, we revisit the notable scheme (Sahai and Waters in STOC ’14) and show it is inherently dual-deniable. Finally, we extend the Boneh-Katz transform to capture CCA security, deriving dual-deniable and CCA-secure PKE from any selectively dual-deniable IBE under multi-TA setting. Overall our work mounts the feasibility of anonymous messaging against coercion attacks. © International Association for Cryptologic Research 2025.

关键词： Anonymity

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ALCencryption:A Secure and Efficient Algorithm for Medical Image Encryption

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computer Modeling in Engineering & Sciences 2020年第12期125卷 1083-1100页

作者： Jiao Ge College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002China

With the rapid development of medical informatization and the popularization of digital imaging equipment,DICOM images contain the personal privacy of patients,and there are security risks in the process of storage and transmission,so it needs to be *** order to solve the security problem of medical images on mobile devices,a safe and efficient medical image encryption algorithm called ALCencryption is *** algorithm first analyzes the medical image and distinguishes the color image from the gray *** gray images,the improved Arnold map is used to scramble them according to the optimal number of iterations,and then the diffusion is realized by the Logistic and Chebyshev map cross-diffusion *** color image is encrypted by cross-diffusion algorithm of double chaotic *** and efficiency analysis show that the ALCencryption algorithm has the characteristics of small neighboring pixels,large key space,strong key sensitivity,high safety and short encryption *** is suitable for medical image encryption of mobile devices with high real-time requirements.

关键词： Patient privacy DICOM medical image encryption scrambling degree cross-diffusion

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Temporal Feature Aggregation for Efficient 2D Video Grounding

Temporal Feature Aggregation for Efficient 2D Video Groundin...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Mohan Chen Yiren Zhang Jueqi Wei Yuejie Zhang Rui Feng Tao Zhang Shang Gao School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University School of Information Management and Engineering Shanghai Key Laboratory of Financial Information Technology Shanghai University of Finance and Economics School of Information Technology Deakin University

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Video grounding aims to locate the target video moment in an untrimmed video based on a text query. Most existing methods employ 3D CNNs as the video feature extractor, incurring substantial computational costs. Only a few methods use 2D backbones for video feature extraction, and they suffer from diminished accuracy due to the inherent lack of temporal information within 2D features. To address this problem, we propose a novel 2D video grounding method called TFA that improves accuracy while minimizing computational costs. Our approach involves a query-guided temporal feature aggregation module designed to explicitly capture temporal information. We disentangle time intervals of input video frames and prediction spans to reduce computational overhead. Additionally, we introduce deformable attention into the multi-modal encoder for further enhancement. Extensive experiments on two public datasets demonstrate that our method outperforms previous 2D video grounding methods and achieves competitive results with most 3D methods at significantly reduced costs.

关键词： Three-dimensional displays Accuracy Costs Grounding Streaming media Feature extraction Computational efficiency

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Zero-shot event-intensity asymmetric stereo via visual prompting from image domain 24

Zero-shot event-intensity asymmetric stereo via visual promp...

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Proceedings of the 38th International Conference on Neural information processing Systems

作者： Hanyue Lou Jinxiu Liang Minggui Teng Bin Fan Yong Xu Boxin Shi State Key Laboratory of Multimedia Information Processing and National Engineering Research Center of Visual Technology School of Computer Science Peking University National Key Laboratory of General AI School of Intelligence Science and Technology Peking University School of Computer Science and Engineering South China University of Technology

ISBN: (纸本)9798331314385

Event-intensity asymmetric stereo systems have emerged as a promising approach for robust 3D perception in dynamic and challenging environments by integrating event cameras with frame-based sensors in different views. However, existing methods often suffer from overfitting and poor generalization due to limited dataset sizes and lack of scene diversity in the event domain. To address these issues, we propose a zero-shot framework that utilizes monocular depth estimation and stereo matching models pretrained on diverse image datasets. Our approach introduces a visual prompting technique to align the representations of frames and events, allowing the use of off-the-shelf stereo models without additional training. Furthermore, we introduce a monocular cue-guided disparity refinement module to improve robustness across static and dynamic regions by incorporating monocular depth information from foundation models. Extensive experiments on real-world datasets demonstrate the superior zero-shot evaluation performance and enhanced generalization ability of our method compared to existing approaches.

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SNIDA: Unlocking Few-Shot Object Detection with Non-Linear Semantic Decoupling Augmentation

SNIDA: Unlocking Few-Shot Object Detection with Non-Linear S...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yanjie Wang Xu Zou Luxin Yan Sheng Zhong Jiahuan Zhou Huazhong University of Science and Technology Wuhan China National Key Laboratory of Multispectral Information Intelligent Processing Technology China Wangxuan Institute of Computer Technology Peking University Beijing China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Once only a few-shot annotated samples are available, the performance of learning-based object detection would be heavily dropped. Many few-shot object detection (FSOD) methods have been proposed to tackle this issue by adopting image-level augmentations in linear manners. Nevertheless, those handcrafted enhancements often suf-fer from limited diversity and lack of semantic awareness, resulting in unsatisfactory performance. To this end, we propose a Semantic-guided Nonlinear Instance-level Data Augmentation method (SNIDA) for FSOD by decoupling the foreground and background to increase their diversities respectively. We design a semantic awareness enhancement strategy to separate objects from backgrounds. Concretely, masks of instances are extracted by an unsupervised semantic segmentation module. Then the diversity of samples would be improved by fusing instances into different backgrounds. Considering the shortcomings of augmenting images in a limited transformation space of existing traditional data augmentation methods, we introduce an object reconstruction enhancement module. The aim of this module is to generate sufficient diversity and nonlinear training data at the instance level through a semantic-guided masked autoencoder. In this way, the potential of data can be fully exploited in various object detection scenarios. Extensive experiments on PASCAL VOC and MS-COCO demonstrate that the proposed method outperforms base-lines by a large margin and achieves new state-of-the-art results under different shot settings.

关键词： computer vision Fuses Semantic segmentation Computational modeling Semantics Training data Object detection

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用于紫外线成像和无线报警的水凝胶基可伸缩、高稳定性和高性能的光电传感器

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Science China Materials 2024年第6期67卷 1926-1937页

作者：洪杰钊姚帝杰王浩丁琼玲罗艺冰于家豪张鹤曾令兴杨柏儒王冰陶凯吴进 State Key Laboratory of Optoelectronic Materials and Technologies and Guangdong Province Key Laboratory of Display Material and Technology School of Electronics and Information TechnologySun Yat-sen UniversityGuangzhou 510275China Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace Northwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Northwestern Polytechnical UniversityShenzhen 518063China State Key Laboratory of Transducer Technology Shanghai 200050China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing National Engineering Research Center of Novel Equipment for Polymer ProcessingKey Laboratory of Polymer Processing Engineering(SCUT)Ministry of EducationSouth China University of TechnologyGuangzhou 510641China Engineering Research Center of Polymer Green Recycling of Ministry of Education College of Environment and ResourcesFujian Normal UniversityFuzhou 350007China State Key Laboratory of Polymer Materials Engineering Sichuan UniversityChengdu 610065China

柔性可穿戴的紫外线探测器在个体紫外线暴露监测、智能仿生眼和军事领域受到广泛关注.然而,传统不可拉伸的材料和器件结构设计限制了设备在可动态变形的人体皮肤和非平面表面上的精确监测应用和稳定附着.在本研究中,我们提出了基于氧化... 详细信息

柔性可穿戴的紫外线探测器在个体紫外线暴露监测、智能仿生眼和军事领域受到广泛关注.然而,传统不可拉伸的材料和器件结构设计限制了设备在可动态变形的人体皮肤和非平面表面上的精确监测应用和稳定附着.在本研究中,我们提出了基于氧化铜/碳-水凝胶-氧化锌/碳的新型应变隔离异质结构的本征可拉伸(拉伸应变或弯曲高达150%)紫外线探测器,该探测器具有高灵敏度(开/关比为2100%)、高稳定性(大于4000次循环),以及快速响应和恢复时间(分别为1.5和4 s).值得注意的是,该探测器通过水凝胶桥在氧化铜/碳和氧化锌/碳电极之间引入的p-n结能带结构,以及离子导电水凝胶中I^(-)/I_(3)^(-)的电化学反应机制,显著提高了其载流子效率和紫外线响应强度.本文通过集成传感器与所设计的电路板,进一步开发了一种无线紫外线报警系统,用于紫外线强度超标警报.此外,本文还设计了一种光电传感器阵列,并将其用作视网膜假体,以实现对环境紫外线强度的实时监测和成像.本文基于水凝胶基异质结构为开发可穿戴、可拉伸的光电紫外线传感器单元和成像阵列提供了一种新的可行方法.

关键词： flexible hydrogel sensors stretchable UV sensors UV imaging array optoelectronic sensors wireless alarm

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FlyLISL: Traffic Balance Awared Routing for Large-scale Mixed-Reality Telepresence over Reconfigurable Mega-Constellation 42

FlyLISL: Traffic Balance Awared Routing for Large-scale Mixe...

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42nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2022

作者： Zhang, Ruoyi Deng, Jing Liu, Qi Xie, Xinlei Gong, Qingyuan Zhu, Chao Beijing Institute of Technology School of Cyberspace Science and Technology China Communication University of China State Key Laboratory of Media Convergence and Communication China School of Information and Electronics Beijing Institute of Technology China School of Computer Science Fudan University Shanghai Key Lab of Intelligent Information Processing China

ISBN: (数字)9781665488792

ISBN: (纸本)9781665488792

With the emerging telepresence applications, such as meta universe, tele-education and tele-social, there exist a large number of demands for sufficient network resources for visual streaming. However, transmitting the huge volume of the generated visual data through the meandering terrestrial networks would overwhelm the backbone networks and cause non-negligible latency. Mega-constellations, such as OneWeb and Starlink, is developing as one of 'New Infrastructure Construction', and could provide high-capacity and low-latency communication in a world-wide range. However, most of the existing mega-constellation networks' topology is fixed and would easily fall into congestion with the bursting traffic generated by the large-scale telepresence applications. To address this challenge, we propose a reconfigurable mega-constellation architecture by utilizing the permanent and temporary laser inter-satellite links (LISLs). Moreover, based on the mixed-integer linear programming (MILP), we design a routing system, FlyLISL, aiming at balancing the global traffic load by minimizing the maximum link utilization of all LISLs. To evaluate the effectiveness of FlyLISL, we simulate the performance of FlyLISL by comparing with the particle swarm optimization (PSO) and Random based routing strategies. Compared with reference works, FlyLISL reduces the maximum link utilization by up to 72.6%. © 2022 IEEE.

关键词： Mixed reality

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面向三频WiFi应用的分集玻璃天线

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Engineering 2023年第4期23卷 157-169,M0007页

作者：胡鹏飞梁国华陆贵文潘咏梅郑少勇 State Key Laboratory of Terahertz and Millimeter Waves and Department of Electrical Engineering City University of Hong KongHong Kong 999077China School of Electronics and Information Technology(School of Microelectronics) Sun Yat-sen UniversityGuangzhou 510006China Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen UniversityGuangzhou 510006China Information and Communication Technology Center CityU Shenzhen Research InstituteShenzhen 518057China School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510630China

本文研究了两种新型极化和模式分集玻璃介质谐振器天线(DRAs),用于三频段(2.4 GHz、5.2 GHz和5.8 GHz)无线保真(WiFi)应用。研究比较了这两种DRAs以及一种新型空间分集玻璃DRA,以确定哪种分集天线最适合WiFi路由器应用。同时,将这三种... 详细信息

本文研究了两种新型极化和模式分集玻璃介质谐振器天线(DRAs),用于三频段(2.4 GHz、5.2 GHz和5.8 GHz)无线保真(WiFi)应用。研究比较了这两种DRAs以及一种新型空间分集玻璃DRA,以确定哪种分集天线最适合WiFi路由器应用。同时,将这三种分集玻璃DRAs与一个商业空间分集单极对进行比较,以评估玻璃DRA在WiFi路由器应用中的性能。在极化分集天线中,采用双端口馈电方案来激发不同的DRA模式,并通过使用阶梯形DRA来调节DRA模式的频率。对于模式分集设计,引入堆叠式DRA来扩展圆锥和正侧向辐射模的带宽。所有三种新型分集天线均得到了实验验证。在实验中,还测量了三种玻璃分集天线和参考空间分集单极子天线的误码率(BER),并对结果进行了比较和讨论。实验结果表明,在三种天线中,极化分集全向DRA具有最稳定的BER。

关键词： Wireless fidelity Diversity antennas Multi-frequency Glass Dielectric resonator antennas Multiple-input multiple-output

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Unleashing Fine-Coarse Curve Perception Via Trunk-Branch Perturbation

Unleashing Fine-Coarse Curve Perception Via Trunk-Branch Per...

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IEEE International Conference on Image processing

作者： Yunxiang Cao Li Chen Yubo Wang Zhida Feng Xiaoming Liu School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Segmenting intricate curve structures like retinal blood vessels, encompassing both fine and coarse details, remains a significant challenge. This work proposes a novel module that divides these complex curve structures into trunks and branches, fuses the input as auxiliary information, and optimizes the breakpoints of different curve parts through losses. In order to balance the redundant information that may lead to model overfitting, a unique feature perturbation strategy is introduced after the backbone decoding process to enhance the model’s robustness to complex curve structure segmentation tasks. Experiments show that this method can effectively distinguish different topological structures of blood vessels and maintain high segmentation accuracy even at blood vessel intersections or breakpoints, which holds immense potential for diverse future applications in image segmentation.

关键词： Measurement Image segmentation Fuses Perturbation methods Blood vessels Retina Robustness

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Distributed Fixed-Time Algorithms for Time-Varying Constrained Optimization Problems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： He, Xing Li, Yue Zhang, Meng Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, the distributed form of the zeroing neural network for solving time-varying optimal problems is put forward. Compared with traditional centralized algorithms, distributed algorithms possess better privacy and scalability. This paper initially proposes a centralized time-varying optimisation algorithm with fixed-time convergence and certain robustness, which is based on the integration-enhanced zeroing neural network. Subsequently, the algorithm is enhanced, and two distributed algorithms are designed separately. Both of these two algorithms have a fixed convergence time and certain robustness. Additionally, this paper utilizes the penalty function approach to handle time-varying optimization problems with inequality constraints, thereby making the algorithm more widely applicable. The effectiveness of the algorithm is verified through several numerical examples, and the applicability of the algorithm is demonstrated by solving the package-level state-of-charge balancing problem. © 2020 IEEE.

关键词： Optimization algorithms

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