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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Qi Feng Debiao He Min Luo Zengxiang Li Kim-Kwang Raymond Choo Key Laboratory of Aerospace Information Security and Trusted Computing School of Cyber Science and Engineering Wuhan University Ministry of Education Wuhan China Digital Research Institute ENN Group Beijing China Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX USA

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

In cryptocurrency and blockchain-based distributed ledgers, transfer of money (digital coins) can be presented as a transaction. Due to the irreversibility nature of blockchain transactions, a single fraudulent use of private key (used to sign transactions) could have significant consequences (e.g. financial loss). Key protection alone is not adequate in protecting cryptocurrencies, and threshold signature is a viable method to avoid fraudulent key usage or key theft. In this paper, we focus on the Edwards-curve digital security algorithm (EdDSA), which has been applied in several cryptocurrencies (e.g. Cardano, Zcash, and Decred) and design the first efficient two-party EdDSA signing protocol. Unlike standard secret sharing, a valid signature is generated using an interactive protocol without the original key ever being exposed. We mathematically prove the security of our proposed protocol. Findings from the performance evalation of the protocol show that it achieves good performance for curve Ed25519, with a single signing operation in the malicious setting taking approximately 3.32 ms between two devices.

关键词： Performance evaluation Privacy Protocols distributed ledger Conferences Cryptocurrency Standards

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Robust multimodal federated learning for non-IID multimodal data with incompleteness

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Future Generation Computer systems 2026年 174卷

作者： Songcan Yu Kaiming Zhu Feiyuan Liang Junbo Wang Krishna Kant Ling Yin Department of Computer Science and Technology Sichuan Police College Luzhou 646000 PR China Police Integration Computing Key Laboratory of Sichuan Province Chengdu 610206 PR China School of Intelligent Systems Engineering Sun Yat-Sen University Shenzhen 518107 PR China Department of Computer and Information Sciences Temple University Philadelphia USA Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 PR China

Federated learning (FL) provides a privacy-aware distributed learning framework using private data belonging to multiple users (or clients). Often the data is generated continuously by the sensors deployed by different clients and is increasingly multimodal. However, the data is invariably imbalanced across different modalities, and certain modalities may even be missing from some clients for certain periods due to sensor failure or unavailability. Furthermore, the available data across clients may not be identically distributed (non-IID). Non-IID data is already known to be a problem with FL, and incomplete modalities could worsen the results even further. Effectively fusing multimodal data with incompleteness and training a high-accuracy global model is still a challenging problem. To tackle this problem, we propose a novel framework called MFedNI that extracts cross-modal temporal features and adaptively adjusts the weights of each modality to mitigate the effect of modal incompleteness. The prototype contrastive learning (PCL)-based feature alignment method further improves the consistency of feature representations across clients. We evaluated MFedNI using two multimodal datasets, HAR and DEAP with different levels of incompleteness. The results demonstrate that MFedNI outperforms other approaches and can train highly accurate models on datasets comprising non-IID multimodal data with incompleteness.

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Individual particle persistence antagonizes global ordering in populations of nematically-aligning self-propelled particles

arXiv

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arXiv 2025年

作者： Nava-Sedeño, Josue Manik Klages, Rainer Hatzikirou, Haralampos Deutsch, Andreas Sevilla, Francisco J. Departmento de Matemáticas Facultad de Ciencias Universidad Nacional Autónoma de México Circuito Exterior Ciudad Universitaria Ciudad de México04510 Mexico Centre for Complex Systems School of Mathematical Sciences Queen Mary University of London Mile End Road LondonE1 4NS United Kingdom London Mathematical Laboratory 8 Margravine Gardens LondonW6 8RH United Kingdom Technische Universität Dresden Center for Information Services and High Performance Computing Nöthnitzer Straße 46 Dresden01062 Germany Mathematics Department Khalifa University PO Box 127788 Abu Dhabi United Arab Emirates Instituto de Física Universidad Nacional Autónoma de México Apdo. Postal 20-364 Ciudad de México01000 Mexico

The transition from individual to collective motion plays a significant role in many biological processes. While the implications of different types of particle-particle interactions for the emergence of particular modes of collective motion have been well studied, it is unclear how particular types of individual migration patterns influence collective motion. Here, motivated by swarming bacteria Myxococcus xanthus, we investigate the combined effects of the individual pattern of migration and of particle-particle interactions, on the emergence of collective migration. We analyze the effects of a feature of individual pattern migration, the persistence of motion, on the collective properties of the system that emerge from interactions among individuals;in particular, when nematic velocity alignment interaction mediates collective dynamics. We find, through computer simulations and mathematical analysis, that an initially disordered migratory state can become globally ordered by increasing either, the particle-particle alignment interaction strength or the persistence of individual migration. In contrast, we find that persistence prevents the emergence of global nematic order when both persistence and nematic alignment are comparatively high. We conclude that behavior at the population level does not only depend on interactions between individuals but also on the individuals’ own intrinsic *** Codes 76A15, 82C22 76A15 © 2025, CC BY.

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Assertion-based approaches to auditing complex elections, with application to party-list proportional elections

arXiv

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arXiv 2021年

作者： Blom, Michelle Budurushi, Jurlind Rivest, Ronald L. Stark, Philip B. Stuckey, Peter J. Teague, Vanessa Vukcevic, Damjan School of Computing and Information Systems University of Melbourne Parkville Australia Cloudical Deutschland GmbH Berlin Germany Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA United States Department of Statistics University of California BerkeleyCA United States Department of Data Science and AI Monash University Clayton Australia Thinking Cybersecurity Pty. Ltd. Melbourne Australia School of Mathematics and Statistics University of Melbourne Parkville Australia Melbourne Integrative Genomics University of Melbourne Parkville Australia

Risk-limiting audits (RLAs), an ingredient in evidence-based elections, are increasingly common. They are a rigorous statistical means of ensuring that electoral results are correct, usually without having to perform an expensive full recount - at the cost of some controlled probability of error. A recently developed approach for conducting RLAs, SHANGRLA, provides a flexible framework that can encompass a wide variety of social choice functions and audit strategies. Its flexibility comes from reducing sufficient conditions for outcomes to be correct to canonical 'assertions' that have a simple mathematical form. Assertions have been developed for auditing various social choice functions including plurality, multi-winner plurality, super-majority, Hamiltonian methods, and instant runoff voting. However, there is no systematic approach to building assertions. Here, we show that assertions with linear dependence on transformations of the votes can easily be transformed to canonical form for SHANGRLA. We illustrate the approach by constructing assertions for party-list elections such as Hamiltonian free list elections and elections using the D'Hondt method, expanding the set of social choice functions to which SHANGRLA applies directly. Copyright © 2021, The Authors. All rights reserved.

关键词： Hamiltonians

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Foundational Competencies and Responsibilities of a Research Software Engineer

arXiv

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arXiv 2023年

作者： Goth, Florian Alves, Renato Braun, Matthias Castro, Leyla Jael Chourdakis, Gerasimos Christ, Simon Cohen, Jeremy Druskat, Stephan Erxleben, Fredo Grad, Jean-Noël Hagdorn, Magnus Hodges, Toby Juckeland, Guido Kempf, Dominic Lamprecht, Anna-Lena Linxweiler, Jan Löffler, Frank Martone, Michele Schwarzmeier, Moritz Seibold, Heidi Thiele, Jan Philipp Waldow, Harald von Wittke, Samantha Institute for Theoretical Physics and Astrophysics University of Würzburg Germany European Molecular Biology Laboratory Heidelberg Germany Cluster of Excellence IntCDC University of Stuttgart Germany ZB MED Information Centre for Life Sciences Cologne Germany School of Computation Information and Technology Technical University of Munich Garching Germany Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany Leibniz University Hannover Department of Cell Biology and Biophysics Computational Biology Germany Imperial College London London United Kingdom Institute for Software Technology Berlin Germany Humboldt-Universität zu Berlin Department of Computer Science Berlin Germany Helmholtz-Zentrum Dresden-Rossendorf Germany Institute for Computational Physics University of Stuttgart Germany Geschäftsbereich IT Charité Universitätsmedizin Berlin Germany The Carpentries United States Heidelberg University Scientific Software Center Germany Institute of Computer Science University of Potsdam Germany Technische Universität Braunschweig Germany Michael Stifel Center Jena Friedrich Schiller University Jena Germany Leibniz Supercomputing Centre Garching Germany Mathematical Modeling and Analysis TU Darmstadt Germany IGDORE Munich Germany Weierstrass Institute Berlin Germany Leibniz University Hannover Institute of Applied Mathematics Scientific Computing Hannover Germany Johann Heinrich von Thünen Institute Centre for Information Management Germany

The term Research Software Engineer, or RSE, emerged a little over 10 years ago as a way to represent individuals working in the research community but focusing on software development. The term has been widely adopted and there are a number of high-level definitions of what an RSE is. However, the roles of RSEs vary depending on the institutional context they work in. At one end of the spectrum, RSE roles may look similar to a traditional research role. At the other extreme, they resemble that of a software engineer in industry. Most RSE roles inhabit the space between these two extremes. Therefore, providing a straightforward, comprehensive definition of what an RSE does and what experience, skills and competencies are required to become one is challenging. In this community paper we define the broad notion of what an RSE is, explore the different types of work they undertake, and define a list of foundational competencies as well as values that outline the general profile of an RSE. Further research and training can build upon this foundation of skills and focus on various aspects in greater detail. We expect that graduates and practitioners will have a larger and more diverse set of skills than outlined here. On this basis, we elaborate on the progression of these skills along different dimensions. We look at specific types of RSE roles, propose recommendations for organisations, and give examples of future specialisations. An appendix details how existing curricula fit into this framework. © 2023, CC BY.

关键词： Computer aided software engineering

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A Generalized Attack on Some Variants of the RSA Cryptosystem 25th

A Generalized Attack on Some Variants of the RSA Cryptosyste...

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25th International Conference on Selected Areas in Cryptography, SAC 2018

作者： Nitaj, Abderrahmane Pan, Yanbin Tonien, Joseph Laboratoire de Mathématiques Nicolas Oresme Université de Caen Normandie Caen France Key Laboratory of Mathematics Mechanization NCMIS Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China School of Computing and Information Technology University of Wollongong Wollongong Australia

ISBN: (纸本)9783030109691

Let be an RSA modulus with unknown factorization. The RSA cryptosystem can be attacked by using the key equation. Similarly, some variants of RSA, such as RSA combined with singular elliptic curves, LUC and RSA with Gaussian primes can be attacked by using the key equation. In this paper, we consider the more general equation and present a new attack that finds the prime factors p and q in the case that u, v and w satisfy some specific conditions. The attack is based on Coppersmith’s technique and improves the former attacks. © 2019, Springer Nature Switzerland AG.

关键词： Factorization

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Aircraft Type Classification in Remote Sensing Images using Deep Learning

Aircraft Type Classification in Remote Sensing Images using ...

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International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS)

作者： Youssef Ben Youssef Mohamed Merrouchi Elhassane Abdelmounim Taoufiq Gadi Interdisciplinary Laboratory of Applied Sciences National School of Applied Sciences Berrechid Morocco Lab computing imaging and modeling of complex systems FST of Settat Hassan first University Settat Morocco Lab of Signal Analysis and Information Processing FST of Settat Hassan first University Settat Morocco

ISBN: (数字)9781728169217

ISBN: (纸本)9781728169224

In aeronautic, redundancy of data is strongly desired to make optimal decisions. A large data source is available with the development of the technology used in remote sensing images. Remote Sensing Image Classification (RSIC) is widely exploited in military and civil fields. To improve the performance of multi-label classification, we addressed the problem of RSIC based on the Convolutional Neural Network (CNN) for remote sensing images of aircraft types. Previous studies have used intensive preprocessing which limits the rate of classification. We improved the network structure to make it more accurate and to limit underfitting or overfitting problems. A recent public dataset called Multi-Type Aircraft Remote Sensing Images (MTARSI) is used in this work to validate our method. Extensive experiments prove the effectiveness of the proposed method in terms of accuracy.

关键词： Aircraft Training Remote sensing Convolution Feature extraction Testing Task analysis

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Random Occlusion Recovery with Noise Channel for Person Re-identification 16th

Random Occlusion Recovery with Noise Channel for Person Re-i...

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16th International Conference on Intelligent computing, ICIC 2020

作者： Zhang, Kun Wu, Di Yuan, Changan Qin, Xiao Wu, Hongjie Zhao, Xingming Zhang, Lijun Du, Yuchuan Wang, Hanli Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Tongji University Shanghai China Guangxi Academy of Science Nanning530025 China School of Computer and Information Engineering Nanning Normal University Nanning530299 China School of Computer Science and Technology Soochow University Suzhou215006 China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China Fudan University Shanghai200433 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai China Collaborative Innovation Center of Intelligent New Energy Vehicle and School of Automotive Studies Tongji University Shanghai201804 China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Department of Transportation Engineering Tongji University Shanghai201804 China Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing and Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

ISBN: (纸本)9783030607982

Person re-identification, as the basic task of a multi-camera surveillance system, plays an important role in a variety of surveillance applications. However, the current mainstream person re-identification model based on deep learning requires a lot of labeled data, which takes a lot of time and manpower. In this study, we proposed a person re-identification method based on random occlusion recovery with noise channel. We add random occlusion blocks to the original image, use the GAN model for repair, and use the repaired image to expand the original training set. After that, the generated image is adjusted through the noise channel. Finally, we use the enhanced data set to train the baseline model. Our model achieves the state-of-the-art on Market-1501 dataset, proving that the method is effective. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Correction to: Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing

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Journal of cloud computing 2025年第1期14卷 1-1页

作者： Zhou, Jincheng Lilhore, Umesh Kumar M, Poongodi Hai, Tao Simaiya, Sarita Abang Jawawi, Dayang Norhayati Alsekait, Deema Mohammed Ahuja, Sachin Biamba, Cresantus Hamdi, Mounir School of Computer and Information and Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Qiannan Normal University for Nationalities Duyun China Department of Computer Science and Engineering Chandigarh University Mohali India College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar School of Computing Faculty of Engineering Universiti Teknologi Malaysia (UTM) Johor Malaysia Department of Computer Science and Information Technology Princess Nourah Bint Abdul Rahman University Applied College Riyadh Saudi Arabia Department of Culture Studies Religious Studies and Educational Sciences University of Gävle Gävle Sweden

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Geo-cloudlet: Time and Power Efficient Geospatial Query Resolution using cloudlet

Geo-Cloudlet: Time and Power Efficient Geospatial Query Reso...

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International Conference on Advanced computing, ICAC

作者： Jaydeep Das Anwesha Mukherjee Soumya K. Ghosh Rajkumar Buyya Advanced Technology Development Centre Indian Institute of Technology Kharagpur West Bengal India Department of Computer Science Mahishadal Raj College Purba Medinipur West Bengal India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne VIC Australia

ISBN: (数字)9781728152868

ISBN: (纸本)9781728152875

Geospatial data analysis is an emerging area of research today due to the potential to enable varied location-aware services. The existing centralized cloud-based analysis becomes time and computing-intensive for huge amount of geospatial data processing. This paper addresses the challenge of time and power-efficiency in QoS-aware geospatial query resolution. We propose a cloudlet based hierarchical paradigm, namely Geo-cloudlet, where the cloudlets contain the geospatial data of the districts. The state and national level geospatial data are stored inside the state cloud and country cloud respectively. The query resolution is performed by either the cloudlet or by the state cloud or country cloud depending upon the geographical region related to the query. The experimental analysis illustrates that the proposed architecture Geo-cloudlet reduces the latency up to 61.3% and power consumption up to 61.1% over the use of only remote cloud servers for geospatial query resolution.

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