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Chinese Automation Congress (CAC)

作者： Jingsi Wang Dong Liu Ran Zheng Yongcai Hu Wu Gao Chen Zhao School of Computer Science Northwestern Polytechnical University Xi’an China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China

Image stitching plays an important role in the field of computer vision and image processing. Although some sophisticated stitching methods have been proposed, they are usually time-consuming. Because many application scenarios, such as video surveillance, need quick image stitching to provide a wide field of view, accelerating the image stitching is critical. In recent years, the neural network is used to stitching images, but only relatively small size images can be processed; meanwhile, time-consuming image stitching is also unavoidable. In this paper, to quickly stitch 1920×1080 images generated by the dual camera system, an image stitching algorithm is proposed. We divided the algorithm depending on its timeliness on different steps, and its time-consuming steps are parallelized on Graphics Processing Unit (GPU) platforms to be accelerated. We tested different hierarchies for organization of threads and access of memory on compute unified device architecture (CUDA) programming, and the final experiment results showed that our algorithm could reach a speedup ratio up to 119x on the Desktop with 3080ti.

关键词： Image registration Neural networks Merging Graphics processing units Organizations Programming Cameras

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UP-SSO: Enhancing the User Privacy of SSO by Integrating PPID and SGX

UP-SSO: Enhancing the User Privacy of SSO by Integrating PPI...

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Advanced Computing and Endogenous security, International Conference on

作者： Chengqian Guo Fan Lang Qiongxiao Wang Jingqiang Lin State Key Laboratory of Information Security Institute of Information Engineering CAS Data Assurance and Communication Security Research Center CAS School of Cyber Security University of Chinese Academy of Sciences School of Cyber Security University of Science and Technology of China

ISBN: (纸本)9781665424509

Single sign-on (SSO) services are widely deployed on the Internet as the identity management and authentication infrastructure. In an SSO system, after authenticated by the identity providers (IdPs), a user is allowed to log into relying parties (RPs) by submitting an identity proof. However, SSO introduces the potential leakage of user privacy, which is indicated by NIST. That is (a) a curious IdP could track a user's all visits to any RPs and (b) collusive RPs could link the user's identities across different RPs, to learn the user's activity profile. NIST suggests that the Pairwise Pseudonymous Identifier (PPID) should be adopted to prevent collusive RPs from linking the same user, as PPID mechanism enables an IdP to provide a user with multiple individual IDs for different RPs. However, PPID mechanism cannot protect users from IdP's tracking, as it still exposes RP identity to IdP. In this paper, we propose an SSO system, named UP-SSO, providing the enhanced PPID mechanism to protect a user's profile of RP visits from both the curious IdP and the collusive RPs by integrating PPID and SGX. It separates an IdP service into two parts, the server-side service and user-side service. The generation of PPID is shifted from IdP server to user client, so that IdP server no longer needs to learn RP ID. The integrity of user client can be verified by IdP through remote attestation. The detailed design of UP-SSO is described in this paper, and the systemic analysis is provided to guarantee its security. We implemented the prototype system of UP-SSO, and the evaluation of the prototype system shows the overhead is modest.

关键词： Performance evaluation Couplings Privacy Protocols Prototypes Authentication NIST

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21 Gbps Source-Independent Quantum Random Number Generator Based on Vacuum Fluctuations

21 Gbps Source-Independent Quantum Random Number Generator B...

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Asia communications and Photonics Conference and Exhibition (ACP)

作者： Yibo Zhu Yiming Bian Jie Yang Yichen Zhang Song Yu State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China Science and Technology on Communication Security Laboratory Institute of Southwestern Communication Chengdu China

We report an ultra-fast quantum random number generator based on detecting vacuum fluctuations without assuming input states. To elimate the effect of classical noise, Toeplitz hash extractor is employed to extract ra... 详细信息

关键词： Fluctuations Elementary particle vacuum Asia Generators Random number generation Photonics

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An Integrated Silicon Photonic Chip for Continuous-Variable Quantum Random Numbers Generator Based on Vacuum Fluctuation

An Integrated Silicon Photonic Chip for Continuous-Variable ...

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2021 International Conference on Advances in Optics and Computational sciences, ICAOCS 2021

作者： Zhu, Menglin Wang, Xiangyu Xu, Bingjie Yu, Song Chen, Ziyang Guo, Hong State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronics and Center for Quantum Information Technology Beijing100871 China Science and Technology on Communication Security Laboratory Institute of Southwestern Communication No. 6 Chuangye Road Chengdu610041 China

The deployment of quantum random number generator in fiber optics is strongly limited in real world applications due to the size of the components and their cost. Here we present a quantum random number generator based on vacuum fluctuation using an optical homodyne detection in silicon photonic chip achieving minimum entropy/bit of 8.5 for 10 bits sample. The produced random numbers have passed all NIST randomness tests. © Published under licence by IOP Publishing Ltd.

关键词： Random number generation

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6th IEEE International Conference on Computer and communications, ICCC 2020

作者： Xie, Yifan Zhou, Wenan Hu, Huamiao Lu, Zhicheng Wu, Mengyuan School of Computer Science Beijing University of Posts and Telecommunications Beijing China Science and Technology on Communication Information Security Control Laboratory Beijing China

ISBN: (纸本)9781728186351

Code similarity detection is one of the important means to maintain the healthy development of the software eco-environment. Early code similarity detection method is mainly based on the code attribute measurement technology, this method can quickly detect more obvious similar parts on small-scale code datasets, but when faced with large-scale datasets or code segments with similar syntax and semantics, the detection performance is not effective. The new code similarity detection technology based on tree-structure representation and machine learning can adapt to different data changes, thus providing new solutions. This paper proposes a new detection method that combines the abstract syntax tree (AST) structure and unsupervised clustering, this new method can improve the detection efficiency of code clustering analysis, because it not only considers the syntax and semantic information of the code, but also reduces the workload of code data preprocessing through unsupervised clustering. © 2020 IEEE.

关键词： Cluster analysis

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Radar Sea Clutter Modeling and Reconstruction Based on Statistical Singularity Power Spectrum 5

Radar Sea Clutter Modeling and Reconstruction Based on Stati...

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5th IEEE International Conference on Signal and Image Processing, ICSIP 2020

作者： Xiong, Gang Huang, Baigang Science and Technology on Communication Information Security Control Lab. Jiaxing China Shanghai Key Lab. for Intelligent Sensing and Recognition Sjtu Shanghai China No.36 Research Institute of Cetc Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781728168968

In this paper, the radar clutter reconstruction model based on singularity power spectrum (SPS) and instantaneous singularity exponent (ISE) is proposed. The proposed ISE-SPS model consists of power measure channel and dimension measure channel. The multi-scale wavelet coefficients are estimated based on the coupling of the two channels to reconstruct the radar sea clutter. Experiment based on the Ice Multi-parameter Imaging X-Band (IPIX) indicates that the proposed model behaves better than the N-partitioned random multiplicative model (NRMM), with about 32% increment in terms of correlation coefficient and normalized MSE of MFS and SPS. © 2020 IEEE.

关键词： Power spectrum

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Constraint-Pareto Dominance and Diversity Enhancement Strategy based Evolutionary Algorithm for Solving Constrained Multiobjective Optimization Problems

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IEEE Transactions on Evolutionary Computation 2025年

作者： Liu, Zhe Han, Fei Ling, Qinghua Han, Henry Jiang, Jing Jiangsu University School of Computer Science and Communication Engineering Zhenjiang212013 China Hefei Comprehensive National Science Center Anhui Energy Laboratory Institute of Energy China Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Zhenjiang212013 China Jiangsu University of Science and Technology School of Computer Science Zhenjiang212003 China Baylor University School of Engineering and Computer Science Waco76798 United States Anqing Normal University School of Computer and Information Anqing246011 China

The utilization of both constrained and unconstrained-based optimization for solving constrained multi-objective optimization problems (CMOPs) has become prevalent among recently proposed constrained multiobjective evolutionary algorithms (CMOEAs). However, the constrained-based optimization which adopted by many CMOEAs typically gives priority to feasible solutions over infeasible ones regardless of their objective values, potentially leading to degraded performance due to the elimination of promising infeasible solutions with strong convergence and diversity. Furthermore, many existing CMOEAs have difficulty in maintaining diversity while focusing on feasibility, thereby hindering their ability to effectively address CMOPs characterized by complex feasible regions. To tackle these challenges, a constraint-Pareto dominance relationship is proposed in this paper to evaluate solutions based on both objectives and feasibility, to improve the optimization potential by reduce the elimination probability of promising infeasible solutions. A diversity enhancement strategy is also designed to enable simultaneously focus on both diversity and feasibility, thus effectively ensuring the diversity of the feasible solutions obtained. Empirical results from benchmark suites and real-world problems demonstrate that our proposed algorithm surpasses state-of-the-art CMOEAs. © 1997-2012 IEEE.

关键词： Optimization algorithms

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Integrated high-performance error correction for continuous-variable quantum key distribution

arXiv

引用

arXiv 2024年

作者： Zhou, Chuang Li, Yang Ma, Li Yang, Jie Huang, Wei Sun, Ao Wang, Heng Luo, Yujie Li, Yong Chen, Ziyang Lau, Francis C.M. Zhang, Yichen Yu, Song Guo, Hong Xu, Bingjie National Key Laboratory of Security Communication Institute of Southwestern Communication Chengdu610041 China College of Computer Science Chongqing University Chongqing400044 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Center for Quantum Information Technology Peking University Beijing100871 China Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China

An integrated error-correction scheme with high throughput, low frame errors rate (FER) and high reconciliation efficiency under low signal to noise ratio (SNR) is one of the major bottlenecks to realize high-performance and low-cost continuous variable quantum key distribution (CV-QKD). To solve this long-standing problem, a novel two-stage error correction method with limited precision that is suitable for integration given limited on-chip hardware resource while maintaining excellent decoding performance is proposed, and experimentally verified on a commercial FPGA. Compared to state-of-art results, the error-correction throughput can be improved more than one order of magnitude given FER © 2024, CC BY.

关键词： Error correction

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Deep generative network for image inpainting with gradient semantics and spatial-smooth attention

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Journal of Visual communication and Image Representation 2024年 98卷

作者： Sheng, Ziqi Xu, Wenbo Lin, Cong Lu, Wei Ye, Long School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Guangzhou510006 China Applied Laboratory of Dig Data and Education Statistics School of Statistics and Mathematics Guangdong University of Finance and Economics Guangzhou510320 China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China

As a powerful forgery operation in the image content security area, image inpainting based on deep generative networks can yield visually appealing outputs but often produces ambiguous artifacts, especially in boundary and high semantic areas. To address this issue, a novel end-to-end network with gradient semantics and spatial-smooth attention (GS-SSA) is proposed, which combines a gradient learning network and an image inpainting network. The gradient learning network is meant to properly anticipate the gradient semantics in the hole region and get a complete gradient semantic map. The image inpainting network utilizes the complete gradient semantic map to better repair the missing pixels and obtain the final inpainting results. Moreover, spatial-smooth attention is introduced into the image inpainting network, considering both the spatial structural relations and the surrounding information in the hole region. Experimental results on public datasets show the superiority of the proposed method, especially in large-hole region tasks. © 2023 Elsevier Inc.

关键词： Semantics

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Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approach

arXiv

引用

arXiv 2023年

作者： Zhao, Zicheng Luo, Linhao Pan, Shirui Nguyen, Quoc Viet Hung Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Department of Data Science and AI Monash University Australia School of Information and Communication Technology Griffith University Australia Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education

Few-shot inductive link prediction on knowledge graphs (KGs) aims to predict missing links for unseen entities with few-shot links observed. Previous methods are limited to transductive scenarios, where entities exist in the knowledge graphs, so they are unable to handle unseen entities. Therefore, recent inductive methods utilize the sub-graphs around unseen entities to obtain the semantics and predict links inductively. However, in the few-shot setting, the sub-graphs are often sparse and cannot provide meaningful inductive patterns. In this paper, we propose a novel relational anonymous walk-guided neural process for few-shot inductive link prediction on knowledge graphs, denoted as RawNP. Specifically, we develop a neural process-based method to model a flexible distribution over link prediction functions. This enables the model to quickly adapt to new entities and estimate the uncertainty when making predictions. To capture general inductive patterns, we present a relational anonymous walk to extract a series of relational motifs from few-shot observations. These motifs reveal the distinctive semantic patterns on KGs that support inductive predictions. Extensive experiments on typical benchmark datasets demonstrate that our model derives new state-of-the-art performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

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