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arXiv 2025年

作者： Tong, Xi Luo, Xing Yang, Jiangxin Cao, Yanpeng Li, Xin State Key Laboratory of Fluid Power and Mechatronic Systems Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou310027 China Section of Visual Computing and Creative Media School of Performance Visualization and Fine Arts Texas A&M University College StationTX77843 United States

Multispectral imaging plays a critical role in a range of intelligent transportation applications, including advanced driver assistance systems (ADAS), traffic monitoring, and night vision. However, accurate visible and thermal (RGB-T) image registration poses a significant challenge due to the considerable modality differences. In this paper, we present a novel joint Self-Correlation and Cross-Correspondence Estimation Framework (SC3EF), leveraging both local representative features and global contextual cues to effectively generate RGB-T correspondences. For this purpose, we design a convolution-transformer-based pipeline to extract local representative features and encode global correlations of intra-modality for inter-modality correspondence estimation between unaligned visible and thermal images. After merging the local and global correspondence estimation results, we further employ a hierarchical optical flow estimation decoder to progressively refine the estimated dense correspondence maps. Extensive experiments demonstrate the effectiveness of our proposed method, outperforming the current state-of-the-art (SOTA) methods on representative RGB-T datasets. Furthermore, it also shows competitive generalization capabilities across challenging scenarios, including large parallax, severe occlusions, adverse weather, and other cross-modal datasets (e.g., RGB-N and RGB-D). Copyright © 2025, The Authors. All rights reserved.

关键词： advanced driver assistance systems

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Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

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Computer Modeling in engineering & Sciences 2024年第9期140卷 2513-2532页

作者： Meng Zhang Xiangyang Luo Ningbo Huang Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou450001China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content *** relationship-based methods represent a classical approach for geolocating social ***,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user *** address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation ***,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among *** are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate *** this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social *** better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure *** algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation *** results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social ***,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.

关键词： User geolocation social media neighborhood geographic distribution structure influence

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Universally composable anonymous password authenticated key exchange

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Science china(Information Sciences) 2017年第5期60卷 153-168页

作者： Xuexian HU Jiang ZHANG Zhenfeng ZHANG Jing XU Trusted Computing and Information Assurance Laboratory Institute of SoftwareChinese Academy of Sciences State Key Laboratory of Mathematical Engineering and Advanced Computing Science and Technology on Information Assurance Laboratory State Key Laboratory of Cryptology

Anonymous password authenticated key exchange(APAKE) is an important cryptographic primitive, through which a client holding a password can establish a session key with a server both authentically and anonymously. Although the server is guaranteed that the client in communication is from a pre-determined group, but the client’s actual identity is protected. Because of their convenience, APAKE protocols have been widely studied and applied to the privacy protection research. However, all existing APAKE protocols are handled in stand-alone models and do not adequately settle the problem of protocol composition, which is a practical issue for protocol implementation. In this paper, we overcome this issue by formulating and realizing an ideal functionality for APAKE within the well-known universal composability(UC) framework, which thus guarantees security under the protocol composition operations. Our formulation captures the essential security requirements of APAKE such as off-line dictionary attack resistance, client anonymity and explicit mutual authentication. Moreover, it addresses the arbitrary probabilistic distribution of passwords. The construction of our protocol, which utilizes SPHF-friendly commitments and CCA2-secure encryption schemes, can be instantiated and proven secure in the standard model, i.e., without random oracle heuristics.

关键词： anonymous password authentication key exchange universal composability provable security standard model

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Extracting hidden messages of MLSB steganography based on optimal stego subset

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Science china(Information Sciences) 2018年第11期61卷 241-243页

作者： Chunfang YANG Xiangyang LUO Jicang LU Fenlin LIU Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing

Dear editor,In recent years, steganalysis researchers have tried their best to extract the hidden messages. For example, under the condition of a known embedding position generator, Liu et al.[1] proposed a collision attack algorithm to recover the stego key of least significant bit (LSB) steganography. Fridrich et al.[2] proposed a chi-squared-test-based method to recover the stego key of LSB steganography for the case of an unknown carrier. Under the condition of multiple stego images embedded into the same positions, Ker [3] first proposed locating the

关键词： LSB

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On s-uniform property of compressing sequences derived from primitive sequences modulo odd prime powers

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Science china(Information Sciences) 2017年第5期60卷 84-95页

作者： Yupeng JIANG Qun-Xiong ZHENG Dongdai LIN State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute

Let Z/（p;） be the integer residue ring modulo pewith p an odd prime and e 2. We consider the suniform property of compressing sequences derived from primitive sequences over Z/（p;）. We give necessary and sufficient conditions for two compressing sequences to be s-uniform with α provided that the compressing map is of the form φ(x;, x;,..., x;) = g(x;) + η(x;, x;,..., x;), where g(x;) is a permutation polynomial over Z/（p） and η is an（e-1）-variable polynomial over Z/（p）.

关键词： compressing map linear recurring sequence primitive sequence permutation polynomial s uniform

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computing Power in the Sky: Digital Twin-assisted Collaborative computing with Multi-UAV Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Chao Han, Yu Zhang, Long Jia, Ziye Zhang, Hongliang Hong, Choong Seon Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Jiangsu Nanjing211111 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Kyung Hee University Department of Computer Science and Engineering Gyeonggi-do Yongin-si17104 Korea Republic of University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The collaboration of computing powers (CPs) among unmanned aerial vehicles (UAVs)-mounted edge servers is essential to handle data-intensive tasks of user equipments (UEs). This paper presents a multi-UAV computing power network (CPN) that orchestrates the CP resources of edge servers to cooperatively process tasks through collaborative computing. Due to the frequent interactions among edge servers and the increased complexities for large-scale task executions, we propose a digital twin (DT)-driven multi-UAV CPN framework, where the aerial DT network is created as a digital replica of the multi-UAV network to assist collaborative computing. A joint optimization problem of the service association, offloading power control, task partitions, CP allocation, and UAV trajectory design is formulated to minimize the long-term average delay of UEs. We use the Lyapunov technique to tackle the long-term energy constraint, forming a tractable optimization problem, which is modeled as a Markov decision process to balance the UAV's deficit queue stability and the UE's task completion delay. A hybrid soft actor-critic based deep reinforcement learning algorithm is developed to optimize the joint design by sampling the hybrid action from the Gumbel and Gaussian distributions. Simulation results verify that the multi-UAV CPN contributes to significant performance gains when supported by DTs. © 2025 IEEE.

关键词： Markov processes

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Improvement in Diversify Active Defense for Web Application by Using Language and Database Heterogeneity 11

Improvement in Diversify Active Defense for Web Application ...

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2017 11th IEEE International Conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： Weichao Li Zheng Zhang Liqun Wang State Key Laboratory of Mathematical Engineering and Advanced Computing

ISBN: (纸本)9781538605349;9781538605332

According to OWASP selected web application Top 10 vulnerabilities in 2013 and 2017,structured query language(SQL)injection is consistently ranked the 1 ***,the protection of SQL injection,which is one of the most prevalent and pernicious security issues,requires ***,there are numerous unknown vulnerabilities and potential threats in *** this case,the active defense based on structural diversity can play an effective role to prevent the hacker from exploiting known or unknown *** on the basis of structural diversity,we propose a modified method,heterogeneous language,combined with heterogeneous database in data storage layer,to establish an active defense model for data *** empirically assess the impact of the vulnerability and conclude by testing the accuracy and performance,showing that our security model can not suffer from the same vulnerability as the unprotected ***,the future work and research direction are discussed.

关键词： Cyberspace security Active defence Heterogeneity Web application Database SQL labeling

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Image Classification for Malware Detection using Extremely Randomized Trees 11

Image Classification for Malware Detection using Extremely R...

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2017 11th IEEE International Conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： Xin Zhou Jianmin Pang Guanghui Liang State Key Laboratory of Mathematical Engineering and Advanced Computing

ISBN: (纸本)9781538605349;9781538605332

With the development of machine learning and computer vision, we combined the image classification and malware detection in this work. Based on the technology of image classification, we achieved the detection of malware, using machine learning. In our work, we visualized the malware as a grayscale image and extracted texture features by Gabor filter. Depend on machine learning, we used extremely randomized trees as the classification and 10-fold cross validation to value it. Compared with GBDT, KNN and RF, experimental results are quite impressive with the accuracy rate of 96.19% and the recall rate of 97.51% on a malware database of 15,781 samples.

关键词： component malware image classification machine learning extremely randomized trees

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Research and Implementation of Reconfigurable Architecture of DES and ZUC 2

Research and Implementation of Reconfigurable Architecture o...

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Yuhan Chen Xuehui Du Wei Xiao Haiyang Zhang State Key Laboratory of Mathematical Engineering and Advanced Computing

Reconfigurable cipher chip has become a research hotspot because of its flexibility, security and good resource utilization. At present, research of reconfigurable cipher chip usually focuses on the s

ISBN: (纸本)9781467389808

关键词： Erbium

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IP-Pealing: A Robust Network Flow Watermarking Method Based on IP Packet Sequence

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Chinese Journal of Electronics 2024年第3期33卷 694-707页

作者： Wangxin FENG Xiangyang LUO Tengyao LI Chunfang YANG State Key Laboratory of Mathematical Engineering and Advanced Computing Key Laboratory of Cyberspace Situation Awareness of Henan Province

Network flow watermarking(NFW) is usually used for flow *** actively modulating some features of the carrier traffic,NFW can establish the correspondence between different network *** the face of strict demands of network traffic tracing,current watermarking methods cannot work efficiently due to the dependence on specific protocols,demand for large quantities of packets,weakness on resisting network channel interferences and so *** this end,we propose a robust network flow watermarking method based on IP packet sequence,called as *** is designed to utilize the packet sequence as watermark carrier with IP identification field which is insensitive to time jitter and suitable for all IP based *** enhance the robustness against packet loss and packet reordering,the detection sequence set is constructed in terms of the variation range of packet sequence,correcting the possible errors caused by the network *** improve the detection accuracy,the long watermark information is divided into several short sequences to embed in turn and assembled during *** a large number of experiments on the Internet,the overall detection rate and accuracy of IP-Pealing reach 99.91% and 99.42%*** comparison with the classical network flow watermarking methods,such as PROFW,IBW,ICBW,WBIPD and SBTT,the accuracy of IP-Pealing is increased by 13.70% to 54.00%.

关键词： Network flow watermarking IP packet sequence Detection sequence set Fast detection Robustness

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