检索结果-内蒙古大学图书馆

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimized Data Storage Algorithm of IoT Based on Cloud Computing in distributed System

Optimized Data Storage Algorithm of IoT Based on Cloud Compu...

引用

Emerging Trends in Industry 4.0 (ETI 4.0)

作者： K.Jaya Deepthi T.Suresh Balakrishnan Prabhakar Krishnan U.Samson Ebenezar Nageshwari Department of AIML Mohan Babu University Tirupati-2 AP India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India IEEE Research Scientist Center for Cyber security Systems and Networks Amrita Vishwa Vidyapeetham Amritapuri-campus India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha University Chennai Tamil Nadu India Department of Computer Science and Engineering CARE College of Engineering Trichy Tamil Nadu

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

IoT and cloud technology are vital for large systems. An improved data storage technique for IoT applications and cloud distribution is described in this research. Scalability, reliability, latency, and resource usage are internal and external to the algorithm. The approach above scales well with work portion or dataset size. The first experiment shows the algorithm scaling perfectly even as IoT devices generate additional data. Experiment 2 proves linear scalability works for 100,000 IoT devices, while Experiment 3 efficiently organizes 1 million data points. It proved the algorithm by tolerating manufactured faults. To ensure data service availability, Experiment 1 tests the system’s operational dependability on node failures and network disturbances. With 0.1% downtime even under challenging conditions, experiment 2 showed the algorithm’s incredible robustness in real-world applications. To improve data organization, this experiment exhibits data consistency when nodes fail. Lower and constant time improves operation safety and reliability. Algorithm 1 shows how the algorithm can quickly answer data queries and keep up with the massive amount of data transfers, supporting low-latency IoT applications. Average data retrieval latency of experiment 2 is 10 ms, which is real-time for vital information. Trial 3 processes data online with a latency <20 ms, providing fast insights for speedy response and decision-making. The adaptive distributed workload uses little resources, making the approach efficient. Exp1 uses distributed nodes to share data and processing, improving task efficiency. In experiment 2, 60% of the CPU, 70% of the Memory tool, and 80% of the Storage system are used, demonstrating platform resource efficiency. Trial 3 provides optimal resource allocation with less than 5% waste, making it an effective system that passes all performance benchmarks.

关键词： Cloud computing Scalability Decision making Memory distributed databases Robustness Real-time systems

来源：评论

学校读者我要写书评

暂无评论

State Derivative Normalization for Continuous-Time Deep Neural networks

引用

IFAC-PapersOnLine 2024年第15期58卷 253-258页

作者： Jonas Weigand Gerben I. Beintema Jonas Ulmen Daniel Görges Roland Tóth Maarten Schoukens Martin Ruskowski Chair of Machine Tools and Control Systems RPTU Kaiserslautern and the German Research Center for Artificial Intelligence Kaiserslautern Germany Control Systems (CS) Group at the Department of Electrical Engineering Eindhoven University of Technology Netherlands. R. Tóth is also affiliated to the Systems and Control Laboratory at the Institute for Computer Science and Control Budapest Hungary Institute for Electromobility RPTU Kaiserslautern Germany

The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state or hidden state derivative of the model estimate, or even of the time interval can lead to numerical and optimization challenges with deep learning based methods. This results in a reduced model quality. In this contribution, we show that these three normalization tasks are inherently coupled. Due to the existence of this coupling, we propose a solution to all three normalization challenges by introducing a normalization constant at the state derivative level. We show that the appropriate choice of the normalization constant is related to the dynamics of the to-be-identified system and we derive multiple methods of obtaining an effective normalization constant. We compare and discuss all the normalization strategies on a benchmark problem based on experimental data from a cascaded tanks system and compare our results with other methods of the identification literature.

关键词： System Identification Continuous-Time Neural Ordinary Differential Equations Nonlinear State-Space

来源：评论

学校读者我要写书评

暂无评论

Solutions for Sustainable and Resilient Communication Infrastructure in Disaster Relief and Management Scenarios

arXiv

引用

arXiv 2024年

作者： Karaman, Bilal Basturk, Ilhan Taskin, Sezai Zeydan, Engin Kara, Ferdi Beyazıt, Esra Aycan Camelo, Miguel Björnson, Emil Yanikomeroglu, Halim Manisa Celal Bayar University Turkey Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada Barcelona08860 Spain Department of Computer Science KTH Royal Institute of Technology Stockholm16440 Sweden Department of Computer Engineering Zonguldak Bulent Ecevit University Zonguldak67100 Turkey IDLab Research Group University of Antwerp - IMEC Belgium

As natural disasters become more frequent and severe, ensuring a resilient communications infrastructure is of paramount importance for effective disaster response and recovery. This disaster-resilient infrastructure should also respond to sustainability goals by providing an energy-efficient and economically feasible network that is accessible to everyone. To this end, this paper provides a comprehensive exploration of the technological solutions and strategies necessary to build and maintain resilient communications networks that can withstand and quickly recover from disaster scenarios. The paper starts with a survey of existing literature and related reviews to establish a solid foundation, followed by an overview of the global landscape of disaster communications and power supply management. We then introduce the key enablers of communications and energy resource technologies to support communications infrastructure, examining emerging trends that improve the resilience of these systems. Pre-disaster planning is emphasized as a critical phase where proactive communication and energy supply strategies can significantly mitigate the impact of disasters. We also explore the essential technologies for disaster response, focusing on real-time communications and energy solutions that support rapid deployment and coordination in times of crisis. The paper then presents post-disaster communication and energy management planning for effective rescue and evacuation operations. The main findings derived from the comprehensive survey are also summarized for each disaster phase. This is followed by an analysis of existing vendor products and services as well as standardization efforts and ongoing projects that contribute to the development of resilient infrastructures. A detailed case study of the Turkiye earthquakes is presented to illustrate the practical application of these technologies and strategies. Finally, we address the open issues and challenges in realizing sust

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Computing Safest $st$-Paths in Backbone networks: Efficiently Solvable Cases and Fast Heuristics

Computing Safest $st$-Paths in Backbone Networks: Efficientl...

引用

International Workshop on Reliable networks Design and Modeling (RNDM)

作者： Balázs Vass Péter Revisnyei Alija Pašíć Department of Telecommunications and Artificial Intelligence (TMIT) Faculty of Electrical Engineering and Informatics (VIK) High Speed Networks Laboratory (HSNLab) Budapest University of Technology and Economics (BME) Budapest Hungary Faculty of Mathematics and Computer Science Babeș-Bolyai University Cluj Napoca Romania HUN-REN-BME Information Systems Research Group Budapest Hungary

ISBN: (数字)9798331518189

ISBN: (纸本)9798331518196

For proper evaluation and optimization of the expected availability of a backbone network service, two related very fundamental modeling and algorithmic questions are the following. 1) Realistically estimate the availability of a given $st$ -path for some source and target pair of communicating nodes $s$ and $t$ , and 2) Find a safest $st$ -path. For these, traditional approaches suppose network element failures are independent. In this paper, we show that, by not considering joint failure probabilities, the traditional approaches may misguess the $st$ -path availabilities and, consequently, the total connection availability, which can lead to more frequent Service Level Agreement (SLA) violations and a financial burden on the Communication Service Provider (CSP). Due to the inconsistent estimations, the supposedly safest paths yielded by these approaches may turn out to be suboptimal. On the positive side, we propose a fast algorithmic approach, that, under some assumptions, returns with a (truly) safest $st$ -path accompanied by its exact expected availability. When the aforementioned assumptions do not hold, in our simulations, the proposed algorithmic scheme proved to be a good heuristic, performing at least as well as the traditional method.

关键词： Computational modeling Heuristic algorithms Conferences Estimation Hazards Computational efficiency Optimization Service level agreements

来源：评论

学校读者我要写书评

暂无评论

Generalized Correspondence Matching via Flexible Hierarchical Refinement and Patch Descriptor Distillation

arXiv

引用

arXiv 2024年

作者： Han, Yu Long, Ziwei Zhang, Yanting Wu, Jin Fang, Zhijun Fan, Rui The School of Computer Science and Technology Donghua University Shanghai201620 China The Department of Electronics and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong SAR Hong Kong Hong Kong Group The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

Correspondence matching plays a crucial role in numerous robotics applications. In comparison to conventional hand-crafted methods and recent data-driven approaches, there is significant interest in plug-and-play algorithms that make full use of pre-trained backbone networks for multi-scale feature extraction and leverage hierarchical refinement strategies to generate matched correspondences. The primary focus of this paper is to address the limitations of deep feature matching (DFM), a state-of-the-art (SoTA) plug-and-play correspondence matching approach. First, we eliminate the pre-defined threshold employed in the hierarchical refinement process of DFM by leveraging a more flexible nearest neighbor search strategy, thereby preventing the exclusion of repetitive yet valid matches during the early stages. Our second technical contribution is the integration of a patch descriptor, which extends the applicability of DFM to accommodate a wide range of backbone networks pre-trained across diverse computer vision tasks, including image classification, semantic segmentation, and stereo matching. Taking into account the practical applicability of our method in real-world robotics applications, we also propose a novel patch descriptor distillation strategy to further reduce the computational complexity of correspondence matching. Extensive experiments conducted on three public datasets demonstrate the superior performance of our proposed method. Specifically, it achieves an overall performance in terms of mean matching accuracy of 0.68, 0.92, and 0.95 with respect to the tolerances of 1, 3, and 5 pixels, respectively, on the HPatches dataset, outperforming all other SoTA algorithms. Our source code, demo video, and supplement are publicly available at ***/GCM. © 2024, CC BY.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Implicit Multi-Scale Swin Transformer Network for Image Denoising

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Zhang, Qi Ding, Yuwei Zhang, Weiqi Zhu, Yian Zhang, Bob Lin, Jerry Chun-Wei Harbin Institute of Technology at Weihai School of Economics and Management Weihai China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China Northwestern Polytechnical University School of Computer Science Xi’an China Northwestern Polytechnical University Yangtze River Delta Research Institute Taicang China University of Macau PAMI Research Group Department of Computer and Information Science Taipa China Department of Distributed Systems and IT Devices Electrical Engineering and Mathematical Sciences Silesian university of technology Poland

Image denoising has been used in various edge computing scenarios such as consumer electronics to improve the image quality and user experience. Existing image denoising methods based on Convolutional Neural networks (CNNs) and vision Transformers achieve good performance by empirically utilizing residual neural network (ResNet) as basic component. However, ResNet lacks interpretability in network design and also long-term memory of features, potentially restricting the performance of denoising networks. In this paper, we propose an Implicit Multi-scale Swin Transformer Network (IMSNet) for image denoising, which introduces the implicit Euler scheme from the feature memory perspective. Specifically, densely connected implicit feature extraction blocks (IFEBs) are designed to learn the residual mapping between noisy and clean images. The IFEB reformulates the initial skip connection of ResNet based on the implicit Euler discretization, providing both network interpretability and long-term memory. In IFEB, the multi-scale swin Transformer block (MSB) is designed as the implicit layer to capture spatial details and non-local contextual information at different scales. Additionally, a cross-layer feature fusion block (CLFF) is proposed to further improve feature reuse capabilities. Compared to existing denoising networks, the extensive experiments demonstrate the superior performance of our IMSNet in various image denoising tasks, and the flexibility in the practical applications with proposed light model on resource-restricted platforms such as consumer electronic devices. © 1975-2011 IEEE.

关键词： Image denoising

来源：评论

学校读者我要写书评

暂无评论

Generalized Correspondence Matching via Flexible Hierarchical Refinement and Patch Descriptor Distillation

Generalized Correspondence Matching via Flexible Hierarchica...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yu Han Ziwei Long Yanting Zhang Jin Wu Zhijun Fang Rui Fan School of Computer Science and Technology Donghua University Shanghai P. R. China Shanghai Research Institute for Intelligent Autonomous Systems the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems Machine Intelligence & Autonomous Systems (MIAS) Group the College of Electronics & Information Engineering Tongji University Shanghai P. R. China Department of Electronics and Computer Engineering The Hong Kong University of Science and Technology P. R. China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

关键词： Performance evaluation Accuracy Semantic segmentation Source coding Image matching Supervised learning Pose estimation

来源：评论

学校读者我要写书评

暂无评论

Modern Computing: Vision and Challenges

arXiv

引用

arXiv 2024年

作者： Gill, Sukhpal Singh Wu, Huaming Patros, Panos Ottaviani, Carlo Arora, Priyansh Pujol, Victor Casamayor Haunschild, David Parlikad, Ajith Kumar Cetinkaya, Oktay Lutfiyya, Hanan Stankovski, Vlado Li, Ruidong Ding, Yuemin Qadir, Junaid Abraham, Ajith Ghosh, Soumya K. Song, Houbing Herbert Sakellariou, Rizos Rana, Omer Rodrigues, Joel J.P.C. Kanhere, Salil S. Dustdar, Schahram Uhlig, Steve Ramamohanarao, Kotagiri Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Center for Applied Mathematics Tianjin University Tianjin China Raygun Performance Monitoring Wellington New Zealand Department of Computer Science York Centre for Quantum Technologies University of York York United Kingdom Microsoft Schiphol Netherlands Distributed Systems Group Vienna University of Technology Vienna Austria Detecon International GmbH Munich Germany Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science University of Western Ontario London Canada Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Institute of Science and Engineering Kanazawa University Japan Tecnun School of Engineering University of Navarra Spain Department of Computer Science and Engineering College of Engineering Qatar University Doha Qatar Bennett University Greater Noida India Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Baltimore United States Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia COPELABS Lusófona University Lisbon Portugal Sydney Australia The University of Melbourne Victoria Australia Laboratory School of Computing and Information Systems The University of Melbourne Australia

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress. © 2024, CC BY.

关键词： Obsolescence

来源：评论

学校读者我要写书评

暂无评论

Accounting for the Special Role of Infrastructure-assisted Collective Perception

Accounting for the Special Role of Infrastructure-assisted C...

引用

International Conference on Intelligent Transportation

作者： Florian Alexander Schiegg Anna–Lisa Rueeck Jörg Gamerdinger Hugues Tchouankem Edmir Xhoxhi Georg Volk Distributed Intelligence and Systems Corporate Research Robert Bosch GmbH Hildesheim Germany Function Development 3D Surround View Engineering Parking Functions Robert Bosch GmbH Feuerbach Germany Department of Computer Science Embedded Systems Group University of Tübingen Tübingen Germany Institute of Communication Technology Leibniz University Hanover Hanover Germany

The number of traffic participants has increased exponentially over the past century, making a traffic accident the most likely cause of death for children and young adults today. Vehicle-to-Everything (V2X) communication is regarded as one of the most promising emerging technologies to enhance road safety. It allows traffic participants to exchange relevant information to increase their environmental perception. Cooperative Awareness, a V2X service that is already being deployed in Europe, enables road users to share their dynamic states. Collective Perception (CP), currently in the final stage of standardization in the different regions of the world, enables the exchange of sensor-detected objects. The latter is thus not only relevant for connected vehicles but can further be used by sensor-equipped infrastructure to support vehicular perception, opening a whole new range of possibilities. The objective of this work is to investigate mechanisms to account for the special role of Infrastructure-assisted Collective Perception (ICP). Packet duplication is introduced for ICP to enhance the communication reliability. Additionally, different message generation rules prioritizing ICP are proposed and compared based on the enabled environmental perception. Simulations show significant improvements of the average precision, reaching an average increase of about 60% for ICP in comparison to V2V -based CP in scenarios with low connected vehicle densities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：