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Research on Trust Management Mechanism in Vehicular Named Data networking 22

Research on Trust Management Mechanism in Vehicular Named Da...

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22nd IEEE international Symposium on Parallel and distributed Processing with Applications, ISPA 2024

作者： Sa, Rula Wang, Haotian Liu, Zhen Yu, Meiju Zhang, Jin Inner Mongolia University College of Computer Science Hohhot China

ISBN: (纸本)9798331509712

VndN (Vehicular Named Data networking) applies completely new communication mechanism to the VANET (Vehicular Ad hoc Network), which can effectively improve the efficiency of vehicle communication and reduce communication overhead. However, the dynamic of the vehicle network topology causes malicious nodes to join the network and send fake messages to legitimate nodes, which brings many security challenges to the reliable communication between vehicles in VndN. Trust management in VndN is mainly used to evaluate the security and reliability of messages and nodes in the network and is an important technical means in the field of security of VANET. In this paper, we proposed a trust management mechanism, including two parts: a fake message detection mechanism based on multi-attribute decision-making and a malicious node detection mechanism based on LSTM (Long Short-Term Memory). Firstly, the fake message in the network is detected by the vehicle node using multiple attributes, and then the malicious node is detected by LSTM based on the multiple features of the node. Finally, the proposed mechanism is tested by using the data obtained from the simulation experiment on the simulation platform. The experimental results show that the mechanism proposed in this paper can effectively improve the detection effect of fake messages and malicious nodes, and build a reliable trust relationship between nodes, thereby improving the security of VndN. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Evaluating Data Trust in Blockchain-Based IoT Systems Using Machine Learning Techniques 22

Evaluating Data Trust in Blockchain-Based IoT Systems Using ...

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22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Ratnayake, Rashmi Liyanage, Madhusanka Murphy, Liam School of Computer Science University College Dublin Ireland

ISBN: (纸本)9798331508050

The convergence of blockchain and Internet of Things (IoT) has become increasingly prevalent recently, as it addresses challenges such as single point of failure and security concerns associated with IoT. Blockchain offers immutable data storage, availability, and transparency, but a significant drawback lies in its inability to verify the truthfulness of the data stored on it. State-of-the-art systems attempting to mitigate this concern often rely on conventional reputation-based approaches, which predominantly evaluate historical data from sensors and neglect the critical assessment of data in real-time. Furthermore, there is limited research on incorporating machine learning (ML) methods to enhance data trustworthiness in blockchain systems. This paper proposes a novel ML-based trust assessment approach that takes into account both historical reputation and real-time data trust-worthiness. Our approach integrates multiple ML models within a blockchain framework using edge servers and validators, effectively functioning as a distributed ensemble to enhance classification accuracy, and contributing to more accurate reputation score calculations. Our results demonstrate significant accuracy gains in distinguishing trustworthy and untrustworthy IoT sensor data in blockchain networks. © 2025 IEEE.

关键词： Trusted computing

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MonkeyGPT: Generative AI in Network Anomaly Detection of Video conference Applications 22

MonkeyGPT: Generative AI in Network Anomaly Detection of Vid...

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22nd IEEE international Symposium on Parallel and distributed Processing with Applications, ISPA 2024

作者： Xu, Junhao He, Dongbiao Zhang, Chen Zhou, Xu Ming, Zhongxing Cui, Laizhong Sangfor Technologies Inc China Shenzhen University College of Computer Science and Software Engineering China China

ISBN: (纸本)9798331509712

The rapid advancement of generative artificial intelligence (GAI) has led to the creation of transformative applications such as ChatGPT, which significantly boosts text processing efficiency and diversifies audio, image, and video content. Beyond digital content creation, GAI's capability to analyze complex data distributions holds immense potential for next-generation networks and communications, especially given the swift rise of video conferencing applications (VCAs). This paper presents a dynamic, real-time method for detecting anomalous network links in video conferencing applications. The proposed tool, MonkeyGPT, generates tracing representations of network activity and trains a large language model from scratch to serve as a detection system based on network traffic data. Unlike traditional methods, MonkeyGPT provides an unrestricted search space and does not rely on predefined rules or patterns, enabling it to detect a wider range of anomalies. We demonstrate the effectiveness of MonkeyGPT as an anomaly detection tool in real-world VCAs. The results indicate that the model possesses strong detection capabilities, achieving an accuracy rate of over 97%. It is applicable to various platforms, including Zoom, Microsoft Teams, Tencent Meeting, and Feishu, showcasing its robust adaptability. © 2024 IEEE.

关键词： Video conferencing

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TOWARDS A MACHINE-LEARNING ARCHITECTURE FOR EFFICIENT RESOURCE MANAGEMENT 20

TOWARDS A MACHINE-LEARNING ARCHITECTURE FOR EFFICIENT RESOUR...

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20th international conference Applied computing, AC 2023 and the 22nd international conference WWW/Internet, ICWI 2023

作者： Kostopoulos, Alexandros Chochliouros, Ioannis P. Vardakas, John Verikoukis, Christos Rahman, Arifur Guevara, Andrea P. Beerten, Robbert Chanclou, Philippe Pryor, Simon Varvarigos, Emmanouel Soumplis, Polyzois Hellenic Telecommunications Organization S.A. 99 Kifissias Avenue Maroussi Athens Greece IQUADRAT Informatica Calle Doctor Rizal 10 Barcelona Spain University of Patras University campus Rio Patras26504 Greece IS-Wireless Ulica Pulawska 45 Warsaw Poland Katholieke Universiteit Leuven Oude Markt 13 Leuven Belgium Orange S.A. Rue Olivier de Serres 78 Paris France Accelleran Heerstraat 12 Geel Belgium Patission 42 Athens Greece

5G mobile networks will soon be available to handle all types of applications and to provide services to massive numbers of users. In this complex and dynamic network ecosystem, an end-to-end performance analysis and optimisation will be "key" features to effectively manage the diverse requirements imposed by multiple vertical industries over the same shared infrastructure. To enable such a challenging vision, the MARSAL EU-funded project (MARSAL, 2021) targets the development and evaluation of a complete framework for the management and orchestration of network resources in 5G and beyond by utilizing a converged optical-wireless network infrastructure in the access and fronthaul/midhaul segments. In this paper, we present the network architecture of the MARSAL, as well as how the cell-free experimentation scenarios are mapped to the considered architecture. © ICWI *** rights reserved.

关键词： distributed cloud

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Fast Flexible Paxos: Relaxing Quorum Intersection for Fast Paxos 21

Fast Flexible Paxos: Relaxing Quorum Intersection for Fast P...

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22nd international conference on distributed computing and networking (ICDCN)

作者： Howard, Heidi Charapko, Aleksey Mortier, Richard Univ Cambridge Cambridge England Univ New Hampshire Durham NH 03824 USA

ISBN: (纸本)9781450389334

Paxos, the de facto standard approach to solving distributed consensus, operates in two phases, each of which requires an intersecting quorum of nodes. Multi-Paxos reduces this to one phase by electing a leader but this leader is also a performance bottleneck. Fast Paxos bypasses the leader but has stronger quorum intersection requirements. In this paper we observe that Fast Paxos' intersection requirements can be safely relaxed, reducing to just one additional intersection requirement between phase-1 quorums and any pair of fast round phase-2 quorums. We thus find that the quorums used with Fast Paxos are larger than necessary, allowing alternative quorum systems to obtain new tradeoffs between performance and fault-tolerance.

关键词： distributed computing distributed consensus Paxos

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Approximation Algorithms and Simulated Annealing Heuristics for Row-and-Column Pruning of Deep Neural Networks 22

Approximation Algorithms and Simulated Annealing Heuristics ...

引用

22nd IEEE international Symposium on Parallel and distributed Processing with Applications, ISPA 2024

作者： Tu, Ping-Han Cheng, Yu-Che Hong, Ding-Yong Liu, Pangfeng Wu, Jan-Jan Institute of Information Science Academia Sinica Taipei Taiwan National Taiwan University Department of Computer Science and Information Engineering Taipei Taiwan National Taiwan University The Graduate Institute of Networking and Multimedia Taipei Taiwan

ISBN: (纸本)9798331509712

Convolutional neural networks (CNNs) have achieved immense success in computer vision and other field of science. Despite the achievements, state-of-the-art CNN models have grown to gigantic sizes that demand a lot of computing power and memory resources. As a model compression technique, parameter pruning can lower the computation and memory a CNN model needs. Previous work has proposed a parameter pruning method, which compresses the neural networks by eliminating the rows and columns of the weight matrices. Removing rows and columns preserves the dense structure of the weight matrix, rather than the sparse structure produced by unstructured pruning. Although row-and-column pruning effectively reduces the model size, making the model as compact as possible without sacrificing accuracy remains a challenge. We prove that the row-and-column pruning problem is an NP-complete problem, and we propose two approximation algorithms that provide solutions within twice the cost of the optimal solution. We also show that the approximation ratio cannot be improved for these two algorithms. Finally, we propose two schemes based on simulated annealing to solve the row-and-column pruning problem. The two proposed schemes improve accuracy by 2.7% and 1.6%, respectively, on the ResNet-18 model with 93% sparsity using the Food-101 dataset. © 2024 IEEE.

关键词： Convolutional neural networks

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Analysis of the Applicability of Cloud computing Scaling Techniques for Real-Time Workloads of Industrial Control Systems 22

Analysis of the Applicability of Cloud Computing Scaling Tec...

引用

22nd IEEE international conference on Industrial Informatics, IndIN 2024

作者： Neumann, Rebekka Frick, Florian Lechler, Armin Verl, Alexander University of Stuttgart Stuttgart Germany

ISBN: (纸本)9798331527471

A key feature of cloud computing is elasticity, which enables resources to be allocated and de-allocated according to dynamic application demands. The evolution of Industrial Control Systems (ICS) is moving towards a distributed converged infrastructure that incorporates computing and communication resources as well as software, replacing dedicated hardware running control applications. While modern ICS and cloud environments share similarities, the corresponding applications differ significantly in their execution models and timing requirements. To enhance the flexibility of ICS, control applications must adapt to changing requirements throughout operation, resulting in varying workloads. The potential for dynamic scaling in ICS is considerable, but is not yet being fully exploited. The objective of this paper is to examine the extent to which state-of-the-art cloud autoscaling concepts are applicable to the scaling of real-time workloads and to propose enhancements to these concepts in order to enable the implementation of dynamic autoscaling of real-time workloads. In conclusion, the fundamental concept of cloud autoscaling can be applied, but must be extended, in particular to ensure deterministic resource provisioning and to improve task isolation in order to guarantee predictable task timing behaviour. © 2024 IEEE.

关键词： Cloud platforms

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Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models 22nd

Federated Learning as a Service for Hierarchical Edge Networ...

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22nd international conference on Service Oriented computing

作者： Gao, Wentao Tavallaie, Omid Chen, Shuaijun Zomaya, Albert Univ Sydney Sch Comp Sci Sydney NSW Australia Univ Oxford Dept Engn Sci Oxford England

ISBN: (纸本)9789819608041;9789819608058

Federated learning (FL) is a distributed Machine Learning (ML) framework that is capable of training a new global model by aggregating clients' locally trained models without sharing users' original data. Federated learning as a service (FLaaS) offers a privacy-preserving approach for training machine learning models on devices with various computational resources. Most proposed FL-based methods train the same model in all client devices regardless of their computational resources. However, in practical Internet of Things (IoT) scenarios, IoT devices with limited computational resources may not be capable of training models that client devices with greater hardware performance hosted. Most of the existing FL frameworks that aim to solve the problem of aggregating heterogeneous models are designed for Independent and Identical distributed (IID) data, which may make it hard to reach the target algorithm performance when encountering non-IID scenarios. To address these problems in hierarchical networks, in this paper, we propose a heterogeneous aggregation framework for hierarchical edge systems called HAF-Edge. In our proposed framework, we introduce a communication-efficient model aggregation method designed for FL systems with two-level model aggregations running at the edge and cloud levels. This approach enhances the convergence rate of the global model by leveraging selective knowledge transfer during the aggregation of heterogeneous models. To the best of our knowledge, this work is pioneering in addressing the problem of aggregating heterogeneous models within hierarchical FL systems spanning IoT, edge, and cloud environments. We conducted extensive experiments to validate the performance of our proposed method. The evaluation results demonstrate that HAF-Edge significantly outperforms state-of-the-art methods.

关键词： Federated Learning as a Service (FLaaS) Model Heterogeneity Edge computing IoT Networks

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An User-Driven Active Way to Push ACL in Software-Defined networking 22nd

An User-Driven Active Way to Push ACL in Software-Defined Ne...

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22nd international conference on Parallel and distributed computing, Applications and Technologies (PDCAT 2021)

作者： Yu, Haisheng Liu, Dong Wang, Wenyong Li, Keqiu Zou, Sai Liu, Zhaobin Liu, Yan Macau Univ Sci & Technol Taipa Macao Peoples R China Univ Elect Sci & Technol China Chengdu Peoples R China BII Grp Beijing Peoples R China Tianjin Univ Tianjin Peoples R China Guizhou Univ Guiyang Peoples R China Dalian Maritime Univ Dalian Peoples R China

ISBN: (纸本)9783030967727;9783030967710

Compared with the traditional network, Software-Defined networking (SDN) provides a more convenient network paradigm to build Access Control List (ACL) application. There has been a few studies focusing on ACL application in SDN up to now, but most of the existing work adopts a reactive way to enforce ACL, resulting in new ACL update can not take effect immediately. In this paper, we propose CLACK, an approach for user-driven centralized ACL in SDN. We implement CLACK on both Floodlight and ONOS controller. The experimental results show that CLACK has a better performance than the existing Floodlight firewall application.

关键词： Access Control List (ACL) Software-Defined networking (SDN) Security Floodlight ONOS

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A Mutual Intrusion Detection System for MANET to Address DDoS attacks using Data Mining Techniques 2

A Mutual Intrusion Detection System for MANET to Address DDo...

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2nd international conference on Sustainable computing and Data Communication Systems, ICSCDS 2023

作者： Bala, K. Renjith, P.N. Latha, M. Santhanalakshmi, S.T. School of Computing Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Tamilnadu Chennai600073 India Department of Computer Science and Engineering VIT Chennai Campus Tamilnadu Chennai600127 India Srm Institute of Science and Technology Department of Information Technology Ramapuram Campus Tamilnadu Chennai600089 India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9781665491990

A type of wireless communication network called a mobile ad hoc network (MANET) is composed of numerous flexible components that can move in any of the network's many directions. The Intrusion Detection System (IDS) is a systematic tool implemented to spot suspicious activity with network malfunctions and sends an alert to the security control center. A malicious effort to interfere with the server's or networks regular operation is acknowledged as a distributed denial-of-service (DDoS). This occurrence causes the networking system's general performance to decline. Certain measures must be put into place to improve efficiency. These DDoS attacks are classified as application layer attacks, protocol attacks, and volumetric attacks in the networking system. The server experiences downtime as a result, and the network's general performance suffers. When resources are brought back into the network, it causes external tension. Data mining methods can be used to find this and fix it. © 2023 IEEE.

关键词： Mobile ad hoc networks

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