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The Adaptive Fault-tolerant Routing Based on an Improved Local Security Information Model of the Exchanged Hypercube 21

The Adaptive Fault-tolerant Routing Based on an Improved Loc...

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21st IEEE international symposium on Parallel and distributed Processing with Applications, 13th IEEE international Conference on Big Data and Cloud Computing, 16th IEEE international Conference on Social Computing and Networking and 13th international Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhang, Yazhi Luo, Chuanwen Wang, Guijuan Zhang, Li Lv, Mengjie Yu, Jiguo Qilu University of Technology School of Computer Science and Technology Jinan China Beijing Forestry University School of Information Science and Technology Beijing China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Nanjing University of Posts and Telecommunications College of Computer Nanjing China Qilu University of Technology Shandong Academy of Sciences Big Data Research Institute Jinan China

ISBN: (纸本)9798350329223

With the increasing amount of computation in high-performance computing, the scale of interconnection networks is becoming larger and larger. It is inevitable that processors or links in the network become faulty. Therefore, it is very important for a processor to understand the security status of itself and neighbors, and then adaptively and reliably communicate. However, the existing security information models consider faulty processors or faulty links separately, and do not consider the situation where both processors and links fail simultaneously. The Exchanged Hypercube is an excellent interconnection network structure which achieves a balance between network functionality and hardware overhead while preserving many excellent properties of the Hypercube. In this paper, we propose an adaptive fault-tolerant routing algorithm of the Exchanged Hypercube based on an improved local security information model, which considers the faulty processors and faulty links simultaneously. This algorithm always can select suitable processors for routing based on the local security information and unsafe coefficients of processors, which greatly reduces the impact of the faulty of networks. The adaptive fault-tolerant routing algorithm of the Exchanged Hypercube network is not only suitable for regular networks but also for heterogeneous networks since the Exchanged Hypercube is a semi regular network. Sufficient experimental results show that the algorithm proposed in this paper has a lower packet loss rate, a higher success rate, and a shorter average path length. © 2023 IEEE.

关键词： Hypercube networks

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A Blockchain-based Intrusion Detection/Prevention systems in IoT Network: A systematic review

A Blockchain-based Intrusion Detection/Prevention Systems in...

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2023 international symposium on Green Technologies and Applications, ISGTA 2023

作者： Shalabi, Khawla Al-Haija, Qasem Abu Al-Fayoumi, Mustafa Department of Cybersecurity King Hussein School of Computing Sciences Prince Sumaya University for Technology PO Box 1438 Amman11941 Jordan Department of Cybersecurity Faculty of Computer & Information Technology Jordan University of Science and Technology PO Box 3030 Irbid22110 Jordan

The Internet of Things (IoT) is an innovative technology used in manufacturing, environmental monitoring, home automation, human health applications, and other fields. IoT devices, however, are susceptible to various security risks. Cyber-attacks on IoT systems can halt the entire system, resulting in data loss. Intrusion Detection systems (IDS) can quickly identify malicious activity that could have compromised the network's performance. Effective IDS and Intrusion Prevention System (IPS) are necessary to protect IoT systems. Blockchain technology presents another innovative method to strengthen security systems against the latest attacks. This paper focuses on conducting a Systematic Literature Review (SLR) on Blockchain-based Intrusion Detection/Prevention systems in IoT networks. We reviewed several relevant blockchain-based IDS and IPS proposed for IoT networks and their mechanisms. The most recent research articles, published between 2017 and 2022, were selected from several databases. Consequently, a comprehensive review of these selected papers sheds light on their techniques, advantages, and drawbacks. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Intrusion detection

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LDVNet: Lightweight and Detail-Aware Vision Network for Image Recognition Tasks in Resource-Constrained Environments 29

LDVNet: Lightweight and Detail-Aware Vision Network for Imag...

引用

29th IEEE international Conference on Parallel and distributed systems, ICPADS 2023

作者： Liu, Yuchen Liang, Hu Qiu, Ran Zhao, Shengrong Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Qilu University of Technology Shandong Academy of Sciences Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350330717

In many underwater application scenarios, recognition tasks need to be executed promptly on computationally limited platforms. However, models designed for this field often exhibit spatial locality, and existing works lack the ability to capture crucial details in images. Therefore, a lightweight and detail-aware vision network (LDVNet) for resource-constrained environments is proposed to overcome the limitations of these approaches. Firstly, in order to enhance the accuracy of target image recognition, we introduce transformer modules to acquire global information, thus addressing the issue of spatial locality inherent in traditional convolutional neural networks (CNNs). Secondly, to maintain the network's lightweight nature, we integrate the transformer module with convolutional operations, thereby mitigating the substantial parameter and floating point operations (FLOPs) overhead. Thirdly, for the efficient extraction of crucial fine-grained details from feature maps, we have devised a channel and spatial attention module (C&SA). This module aids in recognizing intricate and fine-grained visual tasks and enhances image understanding. It is seamlessly integrated into LDVNet with nearly negligible parameter overhead. The experimental results demonstrate that LDVNet outperforms other lightweight networks and hybrid networks in different recognition tasks, while being suitable for resource-constrained environments. © 2023 IEEE.

关键词： Detail-aware Image recognition Lightweight

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Methods of increasing data reliability based on distributed and parallel technologies based on blockchain

Methods of increasing data reliability based on distributed ...

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international Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Makhmadiyarovich, Nazarov Fayzullo Sherzodjon, Yarmatov Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan

ISBN: (纸本)9781032669663

This article examines directions and mechanisms for increasing data reliability in computer networks. Currently, the rapid development of information technologies, the rapid growth of data flow, high-quality data processing carried out in network technologies, and the increase in the volume of data lead to an increase in the problem of data reliability. It is an urgent issue to find solutions based on the use of modern technologies to solve these problems. The simultaneous processing of various types of data in information systems, video, audio, text and digital data, creates big data. The variety of data types in bigdata creates the problem of quality data processing, which greatly affects the reliability of the data. Research shows that breaches of data integrity mainly manifest in three directions. In this case, there is a violation of the reliability of interrelated data in data transmission and storage, in the processing of large volumes of data and in the transcription of video data. It is created due to errors created during data transmission based on artificial and natural redundancy. To solve the mentioned problems, increasing data reliability based on blockchain mechanisms for payment systems in data transmission, increasing data reliability based on error minimization mechanisms in video information systems, and distributed computing and parallel mechanisms in large-scale information systems based on methods of increasing data reliability are researched. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Information systems

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Autonomous Cyber Defense using Graph Attention Network Enhanced Reinforcement Learning 30

Autonomous Cyber Defense using Graph Attention Network Enhan...

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30th IEEE international Conference on Parallel and distributed systems, ICPADS 2024

作者： Shi, Yihang Zhang, Huajun Shi, Lin Xu, Shoukun Changzhou University School of Computer Science and Artificial Intelligence Changzhou China

ISBN: (纸本)9798331515966

Ubiquitous networked hosts and Internet of Things (IoT) devices have enabled critical network applications in both enterprise and industrial environments. However, network threats have proliferated, constantly challenging normal network operations and data security of IoT devices. In facing these challenges, defenders have increasingly adopted Deep Reinforcement Learning (DRL) approaches, aiming to leverage their self-learning and adaptability to bolster network security. Despite these efforts, existing approaches often exhibit significant performance bottlenecks when navigating the complexities of network scenarios. This paper introduces a novel algorithm, the Normalized Graph-Attention Proximal Policy Optimization (NGA-PPO), which synergistically integrates Graph Attention networks (GAT) with the existing Proximal Policy Optimization (PPO) framework. By harnessing a weighted mechanism to amalgamate intricate network connectivity data, NGA-PPO empowers intelligent defense agents to dynamically decipher dependencies and interactions within complex network architectures, thereby facilitating precise and prompt defense actions. Comprehensive experiments within the Yawning Titan network security simulation platform reveal that NGA-PPO outperforms other methods, delivering substantial improvements in performance and exhibiting distinct advantages in robustness and generalization capabilities. Specifically, as network scenarios become more complex, existing algorithms face significant performance limitations, whereas NGA-PPO consistently demonstrates high performance, thereby affirming its efficacy and viability in mitigating complex network threats. © 2024 IEEE.

关键词： Reinforcement learning

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PsyLink: User Identity Linkage via Psychological Characteristic Modeling 29

PsyLink: User Identity Linkage via Psychological Characteris...

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29th IEEE international Conference on Parallel and distributed systems, ICPADS 2023

作者： Ma, Xingkong Qiu, Houjie Li, Shaoyong Yao, Shujia Liu, Bo Lin, Wangqun National University of Defense Technology College of Computer Changsha China Shanxi University Taiyuan China Academy of Military Sciences Beijing China

ISBN: (纸本)9798350330717

User identity linkage aims to correlate multiple virtual identities of the same person across different social networks. It is widely used in person profile integration, potential friend recommendation, user behavior prediction, identity verification, etc. Since the data inconsistency and network heterogeneity among social networks, extracting features from profiles, contents, and network structures may lead to severe random noises. To this end, we propose PsyLink, a user identity linkage method via psychological characteristic modeling. To reduce the data noise, PsyLink extracts both internal personality characteristics and external interest characteristics to represent an individual. Furthermore, we design a neighborhood enhancement strategy to capture latent higher-order structural features through a graph contrastive learning technique. Under various parameter settings, the experimental results demonstrate that the macro-f1 of PsyLink improves 19.23% on average compared with state-of-the-art deep learning models. Combined with the psychological characteristics and graph contrastive learning, PsyLink is able to adequately learn the similarities and differences between user identities across social networks. © 2023 IEEE.

关键词： Graph Contrastive Learning Neighborhood Enhancement Psychological Characteristic Modeling User Identity Linkage

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Achieving Latency-Aware V2V Communication with distributed Antenna systems 35

Achieving Latency-Aware V2V Communication with Distributed A...

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35th IEEE international symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Shukla, Vishakha Tchouankem, Hugues Robert, Joerg Robert Bosch GmbH Corporate Research Hildesheim Germany Institute for Information Technology Technische Universität Ilmenau Ilmenau Germany

ISBN: (纸本)9798350362244

The future of accident-free road mobility hinges on reliable Vehicle-to-Vehicle (V2V) communication, especially as autonomous vehicles become more prevalent. The potential of the distributed Antenna systems (DAS) to improve throughput, data rates, and overall network efficiency has been well investigated and proved. However, its performance, especially in latency-aware dense vehicular networks, has not been studied. In this paper, we investigate the performance gain of DAS by equipping the vehicles with three antenna elements mounted on the roof and the bumpers. This results in a significant enhancement of communication reliability. Due to its low complexity and ease of implementation, the DAS relies on the use of selection combining technique allowing the exploitation of the most robust signal received by the antenna elements. Extensive system-level simulations for a highway scenario show that the DAS can significantly improve communication robustness and reliability, especially in scenarios with a large number of communicating vehicles. By effectively harnessing data from both antenna configurations, our study reveals an almost 60 % improvement in terms of the achieved packet loss rate. Moreover, insights gained in this study could be used to support the trade-off analysis between additional antenna costs and V2V communication performance. © 2024 IEEE.

关键词： Packet loss

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Architecting Space Microdatacenters: A System-level Approach 31

Architecting Space Microdatacenters: A System-level Approach

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31st IEEE international symposium on High Performance computer Architecture, HPCA 2025

作者： Bleier, Nathan Eason, Rick Lembeck, Michael Kumar, Rakesh University of Michigan Department of Electrical Engineering & Computer Science Ann ArborMI United States University of Illinois Department of Electrical and Computer Engineering UrbanaIL United States University of Illinois Department of Aerospace Engineering UrbanaIL United States

ISBN: (纸本)9798331506476

Server-based computing in space has been recently proposed due to potential benefits in terms of capability, latency, security, sustainability, and cost. Despite this, there has been no work asking the question: how should we architect systems for server-based computing in space when considering overall cost. This paper presents a Total Cost of Ownership (TCO)-based approach to architecture of server-based computing systems for space (Space Microdatacenters - SμDC) for processing data produced by low Earth orbit (LEO)-based Earth observation (EO) satellites. We show that power of compute is the primary factor in determining SμDC TCO, though the dependence is sublinear. Second, the impact of compute mass, monetary cost, and communication on TCO is relatively insignificant. Third, architectures with the highest \frac{\text { FLOPs }}{W} provide much higher performance per TCO {\} even if they have poor \frac{FLOPs}{\}. We leverage these insights to advocate extreme heterogeneity designs for SμDCs. These designs reduce SμDC TCO by 116× in spite of poor \frac{{FLOPs}}{\} characteristics. We also show that (a) collaborative compute constellations - constellations in which EO satellites are also equipped with compute hardware - further improve SμDC TCO by 1.31 to 1.74×, (b) a distributed architecture reduces TCO by 10% over a monolithic architecture, and (c) low monetary cost of compute can be leveraged to provide near zero cost compute overprovisioning which improves an SμDC's availability significantly and supports graceful degradation. Overall, this is the first paper on cost-aware architecture and optimization of a SμDC. © 2025 IEEE.

关键词： Digital storage

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Enhancing Efficiency and Privacy in distributed Machine Learning: A Comparative Analysis of Federated Learning and Split Learning Techniques 1

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13th international Conference on Information systems and Advanced Technologies, ICISAT 2023

作者： Bouramoul, Imed Eddine Zertal, Soumia Derdour, Makhlouf Computer Sciences Department LIAOA Laboratory University of Oum El Bouaghi Oum El Bouaghi Algeria

ISBN: (数字)9783031605918

ISBN: (纸本)9783031605901

As the volume of data generated by individuals and organizations continues its exponential grow, the need for efficient and secure Machine Learning (ML) algorithms has become increasingly important. Federated Learning (FL) and Split Learning (SL) are two innovative approaches designed to tackle these issues by allowing ML models to be trained using decentralized data sources while preserving data privacy. In this paper, we present a comparative analysis of FL and SL, focusing on their strengths and weaknesses in terms of accuracy, efficiency, and security. We also discuss their potential applications in various domains. Our analysis provides insights into the trade-offs between these two techniques and helps researchers and practitioners make informed decisions when choosing the appropriate approach for their specific use case. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Federated learning

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Federated Orchestration Framework for Integrated Core and Edge Network Security: Combining P4-ShieldNet and SAFE-CAST

Federated Orchestration Framework for Integrated Core and Ed...

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2024 IEEE international Conference on Big Data, BigData 2024

作者： Tuncel, Yusuf Kursat Oztoprak, Kasim Konya Food and Agriculture University Department of Computer Engineering Konya Turkey

ISBN: (纸本)9798350362480

This paper introduces a Federated Orchestration Framework that integrates P4-ShieldNet for core network security with SAFE-CAST for edge security, addressing the complex challenges in modern telecommunication networks. Our approach combines programmable data planes with distributed intelligence, providing a comprehensive security solution from core to edge. Simulations demonstrate significant improvements over traditional methods and standalone implementations, achieving 97% threat detection accuracy, 80% faster response times, and support for up to 50,000 devices. The framework incorporates cross-domain security coordination, federated learning, and intent-based policies, paving the way for adaptive, self-defending networks suitable for next-generation 5G and 6G infrastructures. © 2024 IEEE.

关键词： 5G mobile communication systems

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