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arXiv 2024年

作者： Zhao, Zhouxiang Yang, Zhaohui Chen, Mingzhe Zhang, Zhaoyang Xu, Wei Huang, Kaibin College of Information Science and Electronic Engineering Zhejiang University China Hangzhou310027 China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

Space-air-ground integrated networks (SAGINs) are emerging as a pivotal element in the evolution of future wireless networks. Despite their potential, the joint design of communication and computation within SAGINs remains a formidable challenge. In this paper, the problem of energy efficiency in SAGIN-enabled probabilistic semantic communication (PSC) system is investigated. In the considered model, a satellite needs to transmit data to multiple ground terminals (GTs) via an unmanned aerial vehicle (UAV) acting as a relay. During transmission, the satellite and the UAV can use PSC technique to compress the transmitting data, while the GTs can automatically recover the missing information. The PSC is underpinned by shared probability graphs that serve as a common knowledge base among the transceivers, allowing for resource-saving communication at the expense of increased computation resource. Through analysis, the computation overhead function in PSC is a piecewise function with respect to the semantic compression ratio. Therefore, it is important to make a balance between communication and computation to achieve optimal energy efficiency. The joint communication and computation problem is formulated as an optimization problem aiming to minimize the total communication and computation energy consumption of the network under latency, power, computation capacity, bandwidth, semantic compression ratio, and UAV location constraints. To solve this non-convex non-smooth problem, we propose an iterative algorithm where the closed-form solutions for computation capacity allocation and UAV altitude are obtained at each iteration. Numerical results show the effectiveness of the proposed algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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Global solution to sensor network localization: A non-convex potential game approach and its distributed implementation

arXiv

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arXiv 2024年

作者： Xu, Gehui Chen, Guanpu Hong, Yiguang Fidan, Baris Parisini, Thomas Johansson, Karl H. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures StockholmSE-10044 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China The Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Consider a sensor network consisting of both anchor and non-anchor nodes. We address the following sensor network localization (SNL) problem: given the physical locations of anchor nodes and relative measurements among all nodes, determine the locations of all non-anchor nodes. The solution to the SNL problem is challenging due to its inherent non-convexity. In this paper, the problem takes on the form of a multi-player nonconvex potential game in which canonical duality theory is used to define a complementary dual potential function. After showing the Nash equilibrium (NE) correspondent to the SNL solution, we provide a necessary and sufficient condition for a stationary point to coincide with the NE. An algorithm is proposed_ to reach the NE and shown to have convergence rate O(1/√k). With the aim of reducing the information exchange within a network, a distributed algorithm for NE seeking is implemented and its global convergence analysis is provided. Extensive simulations show the validity and effectiveness of the proposed approach to solve the SNL problem. Copyright © 2024, The Authors. All rights reserved.

关键词： Game theory

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The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption 30

The Power of Bamboo: On the Post-Compromise Security for Sea...

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30th Annual Network and Distributed System Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed System Security Symposium, NDSS 2023. All Rights Reserved.

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Static Performance and Reliability of 4H-SiC Diodes with P+ Regions Formed by Various Profiles and Temperatures

Static Performance and Reliability of 4H-SiC Diodes with P+ ...

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2022 IEEE International Reliability Physics Symposium, IRPS 2022

作者： Mancini, Stephen A. Yup Jang, Seung Chen, Zeyu Kim, Dongyoung Lynch, Justin Liu, Yafei Raghothamachar, Balaji Kang, Minseok Agarwal, Anant Mahadik, Nadeemullah Stahlbush, Robert Dudley, Michael Sung, Woongje State University of New York Polytechnic Institute College of Nanoscale Science and Engineering AlbanyNY12203 United States Stony Brook University Department of Material Science and Chemical Engineering Stony BrookNY11794 United States The Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States Naval Research Laboratory WashingtonDC20375 United States

ISBN: (纸本)9781665479509

Several designs of 1.2kV-rated 4H-SiC PiN diodes and Junction Barrier Schottky (JBS) diodes have been successfully fabricated with various P+ implantation conditions resulting in different junction profiles. P+ regions were implanted at both room temperature and elevated temperature (600C) to monitor the generation of Basal Plane Dislocations (BPDs) and study their impact on device long term reliability. It was found that, when the dose in the deeper portion of the junction (implemented by high energy implantations) is well suppressed, static and long-term reliability performances of room temperature implanted devices can be maintained similar to those of high temperature implanted devices. © 2022 IEEE.

关键词： Room temperature

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Terahertz-mediated microwave-to-optical transduction

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Physical Review A 2024年第4期109卷 042409-042409页

作者： Furkan Sahbaz James N. Eckstein Dale J. Van Harlingen Simeon I. Bogdanov Department of Electrical and Computer Engineering and Nick Holonyak Jr. Micro and Nanotechnology Laboratory University of Illinois at Urbana-Champaign Urbana Illinois 60801 USA Illinois Quantum Information Science and Technology Center University of Illinois Urbana-Champaign Urbana Illinois 61801 USA Department of Physics and Materials Research Laboratory University of Illinois at Urbana Champaign Urbana Illinois 81801 USA

Transduction of quantum signals between the microwave and the optical ranges will unlock powerful hybrid quantum systems enabling information processing with superconducting qubits and low-noise quantum networking through optical photons. Most microwave-to-optical quantum transducers suffer from thermal noise due to pump absorption. We analyze the coupled thermal and wave dynamics in electro-optic transducers that use a two-step scheme based on an intermediate frequency state in the THz range. Our analysis, supported by numerical simulations, shows that the two-step scheme operating with a continuous pump offers near-unity external efficiency with a multiorder noise suppression compared to single-step transduction. As a result, two-step electro-optic transducers may enable quantum-noise-limited interfacing of superconducting quantum processors with optical channels at MHz-scale bit rates.

关键词： Nonlinear optics Quantum engineering Quantum information architectures & platforms Quantum information with hybrid systems Quantum optics Terahertz techniques

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Smart grid security through fusion-enhanced federated learning against adversarial attacks

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engineering Applications of Artificial Intelligence 2025年 157卷

作者： Shabbir, Attia Manzoor, Habib Ullah Zoha, Ahmed Halim, Zahid Faculty of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Topi Pakistan James Watt School of Engineering University Of Glasgow GlasgowG12 8QQ United Kingdom Department of Electrical Engineering University of Engineering and Technology Lahore Pakistan Machine Intelligence and Affective Systems Laboratory National Yunlin University of Science and Technology 123 University Road Section 3 Douliu Yunlin64002 Taiwan

The proliferation of smart grids introduces significant challenges for energy networks in managing and securing the vast data they generate. Federated Learning (FL) provides a cost-effective and privacy-preserving framework for distributed model training, addressing critical concerns around customer data privacy and security. However, FL remains vulnerable to adversarial threats, particularly data poisoning attacks, which can significantly impair model performance. This study presents a novel data poisoning attack and proposes a mitigation framework tailored for resource-constrained smart grids. The Centroid-Based Anomaly Aware Federated Averaging (CBAA-FedAvg) framework is introduced, achieving a Mean Absolute Percentage Error (MAPE) of 2.7 percent, closely aligning with baseline performance while maintaining robustness. CBAA-FedAvg integrates advanced fusion techniques, including parameter quantization (from 32-bit floating point to 8-bit fixed point) and dynamic clustering, to minimize computational complexity and optimize data processing. Furthermore, an automatic stopping criterion optimizes convergence, reducing energy consumption and computation time. Experimental results demonstrate that CBAA-FedAvg exhibits remarkable resilience to both data and model poisoning attacks, leveraging fusion strategies to enhance security and efficiency. This framework provides a scalable and effective solution for improving the fusion, security, and operational efficiency of smart grids. © 2025

关键词： Federated learning

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Transmissive RIS-Empowered LEO-Satellite Communications With Hybrid-NOMA Under Residual Hardware Impairments

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年

作者： Asif, Muhammad Bao, Xu Ali, Zain Ihsan, Asim Ahmed, Manzoor Li, Xingwang Jiangsu University School of Computer Science and Communication Engineering Zhenjiang China University of California Department of Electrical and Computer Engineering Santa CruzCA United States University of Cambridge Department of Engineering CambridgeCB3 0FA United Kingdom Hubei Engineering University School of Computer and Information Science The Institute for AI Industrial Technology Research Xiaogan432000 China Henan Polytechnic University School of Physics and Electronic Information Engineering China Jiaozuo Key Laboratory of Crow-Sensing Network Jiaozuo454003 China

This manuscript introduces an efficient resource allocation framework for a transmissive reconfigurable intelligent surface (T-RIS) assisted Low Earth Orbit (LEO) satellite non-orthogonal multiple access (NOMA) system under residual hardware impairments (RHIs) resulting from imperfect transceiver hardware design. In particular, the goal is to maximize the sum rate of the considered multi-cluster based T-RIS assisted LEO-satellite NOMA network. This is achieved by optimizing the power-allocation of users, time-allocation for each cluster, and transmit passive beamforming of T-RIS node, while adhering to quality-of-service (QoS), time-allocation, and power-budget constraints. Moreover, the presented optimization algorithm tackles the considered highly non-convex problem in three steps. Firstly, the power-allocation of NOMA users is computed by exploiting Lagrange duality and sub-gradient methods. Secondly, the time-allocation for each cluster is determined based on the interior point method by exploiting Mosek-assisted CVX toolbox. Thirdly, the computation of passive beamforming employs semi-definite programming (SDP) and successive convex approximation (SCA) techniques, where a rank-1 solution is achieved by incorporating the Gaussian randomization method. Finally, numerical simulations affirm the effectiveness of the proposed optimization strategy, highlighting its superior performance in comparison to benchmark techniques. Notably, it proves to be highly effective in achieving fast convergence with only a few iterations. © 2017 IEEE.

关键词： Budget control

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Enhanced Redundant Scheme Based on Weighted Cluster-Head Selection for Critical 6G Infrastructures

Enhanced Redundant Scheme Based on Weighted Cluster-Head Sel...

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IEEE Globecom Workshops

作者： Grace Khayat Constandinos X Mavromoustakis Andreas Pitsillides Jordi Mongay Batalla Evangelos K. Markakis Andreas Andreou Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg Warsaw University of Technology Warsaw Poland Department of Electrical and Computer Engineering Hellenic Mediteranean University Estavromenos Heraklion Greece Department of Computer Science Research Foundation University of Nicosia and University of Nicosia Nicosia Cyprus

ISBN: (纸本)9781665459761

Flying Ad hoc Network (FANET) consists of a group of unmanned aerial vehicles (UAVs) that fulfill a certain mission in various applications. The UAV targets uploading data to the 6G networks through communication to other UAVs or to the base station. UAVs collaborate for a purpose to achieve a certain mission in a faster and more reliable way compared to a single UAV. In critical cases such as flooding or earthquakes, one or more UAVs can be non-functional thus emerging a disconnected network. One of the most reliable routing schemes is clustering which splits the network into clusters. Every cluster incorporates a cluster-head and cluster-members. The selection of the cluster-head possesses a high influence on the routing scheme’s performance as it is responsible for all intra-cluster communication. A new clustered weighted scheme with a redundant cluster-head is proposed to ensure end-to-end communication in critical 6G infrastructures. The parameters of the weighted formula used for cluster establishment and primary cluster-head selection are the distance, the performance index, the speed, and the energy. A secondary cluster-head that automatically replaces the primary cluster-head whenever it is non-functional is selected based on the link reliability. The promising results obtained from MATLAB simulation are discussed in section IV.

关键词： 6G mobile communication Base stations Conferences Earthquakes Routing Autonomous aerial vehicles Ad hoc networks

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Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection

arXiv

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arXiv 2023年

作者： Wu, Yunan Castro-Macías, Francisco M. Morales-Álvarez, Pablo Molina, Rafael Katsaggelos, Aggelos K. Image and Video Processing Laboratory Department of Electrical and Computer Engineering Northwestern University United States Department of Computer Science and Artificial Intelligence University of Granada Spain Department of Statistics and Operations Research University of Granada Spain University of Granada Spain

Multiple Instance Learning (MIL) has been widely applied to medical imaging diagnosis, where bag labels are known and instance labels inside bags are unknown. Traditional MIL assumes that instances in each bag are independent samples from a given distribution. However, instances are often spatially or sequentially ordered, and one would expect similar diagnostic importance for neighboring instances. To address this, in this study, we propose a smooth attention deep MIL (SA-DMIL) model. Smoothness is achieved by the introduction of first and second order constraints on the latent function encoding the attention paid to each instance in a bag. The method is applied to the detection of intracranial hemorrhage (ICH) on head CT scans. The results show that this novel SA-DMIL: (a) achieves better performance than the non-smooth attention MIL at both scan (bag) and slice (instance) levels;(b) learns spatial dependencies between slices;and (c) outperforms current state-of-the-art MIL methods on the same ICH test set. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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A Multi-Model Framework to Explore ADHD Diagnosis from Neuroimaging Data

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Journal of Data science 2024年第2期22卷 191-207页

作者： Ozdemir, Yagmur Yavuz Nukala, Naga Chandra Padmini Molinari, Roberto Deshpande, Gopikrishna Department of Mathematics and Statistics Auburn University Auburn AL United States AU MRI Research Center Department of Electrical and Computer Engineering Auburn University Auburn AL United States Department of Psychological Sciences Auburn University Auburn AL United States Alabama Advanced Imaging Consortium Auburn AL United States Center for Neuroscience Auburn University Auburn AL United States School of Psychology Capital Normal University Beijing China Key Laboratory for Learning and Cognition Capital Normal University Beijing China Department of Psychiatry National Institute of Mental Health and Neurosciences Karnataka India Centre for Brain Research Indian Institute of Science Bangalore India Department of Heritage Science and Technology Indian Institute of Technology Hyderabad India

Attention Deficit Hyperactivity Disorder (ADHD) is a frequent neurodevelopmental disorder in children that is commonly diagnosed subjectively. The objective detection of ADHD based on neuroimaging data has been a complex problem with low ranges of accuracy, possibly due to (among others) complex diagnostic processes, the high number of features considered and imperfect measurements in data collection. Hence, reliable neuroimaging biomarkers for detecting ADHD have been elusive. To address this problem we consider a recently proposed multi-model selection method called Sparse Wrapper AlGorithm (SWAG), which is a greedy algorithm that combines screening and wrapper approaches to create a set of low-dimensional models with good predictive power. While preserving the previous levels of accuracy, SWAG provides a measure of importance of brain regions for identifying ADHD. Our approach also provides a set of equally-performing and simple models which highlight the main feature combinations to be analyzed and the interactions between them. Taking advantage of the network of models resulting from this approach, we confirm the relevance of the frontal and temporal lobes as well as highlight how the different regions interact to detect the presence of ADHD. In particular, these results are fairly consistent across different learning mechanisms employed within the SWAG (i.e. logistic regression, linear and radial-kernel support vector machines) thereby providing population-level insights, as well as delivering feature combinations that are smaller and often perform better than those that would be used if employing their original versions directly. © 2024 The Author(s).

关键词： automated detection functional magnetic resonance imaging interpretability prediction accuracy SWAG

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