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检索条件"任意字段=IEEE 34th Conference on Local Computer Networks"

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2009 ieee 34th conference on local computer networks, LCN 2009

2009 IEEE 34th Conference on Local Computer Networks, LCN 20...

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2009 ieee 34th conference on local computer networks, LCN 2009

ISBN: (纸本)9781424444885

the proceedings contain 168 papers. the topics discussed include: stealthy dissemination in intruder tracking sensor networks;evaluation of authentication signaling loads in 3GPP LTE/SAE networks;a localized and distributed channel assignment scheme for wireless mesh networks;algorithms to minimize channel interference in multiple channels multiple interfaces environment;backbone MAC for energy-constrained wireless sensor networks;PiRAT: pivot routing for alarm transmission in wireless sensor networks;CSR: convex subspace routing protocol for WSNs;deploying a real ieee 802.11e testbed to validate simulation results;a polling method using orthogonal signaling for wireless local area networks;an inherently anomaly-free iBGP architecture;a scalable cluster distributed BGP architecture for next generation routers;and optimization bandwidth sharing for multimedia transmission supporting scalable video coding.

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the 34th annual ieee conference on local computer networks (LCN)

The 34th annual IEEE conference on Local Computer Networks (...

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conference on local computer networks (LCN)

conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. this may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original conference proceedings.

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NI-GDBA: Non-Intrusive Distributed Backdoor Attack Based on Adaptive Perturbation on Federated Graph Learning 34

NI-GDBA: Non-Intrusive Distributed Backdoor Attack Based on ...

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34th ACM Web conference, WWW 2025

作者： Li, Ken Shi, Bin Wei, Jiazhe Dong, Bo School of Computer Science and Technology Xi’an Jiaotong University Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi’an China School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an China School of Distance Education Xi’an Jiaotong University Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an China

ISBN: (纸本)9798400712746

Federated Graph Learning (FedGL) is an emerging Federated Learning (FL) framework that learns the graph data from various clients to train better Graph Neural networks(GNNs) model. Owing to concerns regarding the security of such framework, numerous studies have attempted to execute backdoor attacks on FedGL, with a particular focus on distributed backdoor attacks. However, all existing methods posting distributed backdoor attack on FedGL only focus on injecting distributed backdoor triggers into the training data of each malicious client, which will cause model performance degradation on original task and is not always effective when confronted with robust federated learning defense algorithms, leading to low success rate of attack. What’s more, the backdoor signals introduced by the malicious clients may be smoothed out by other clean signals from the honest clients, which potentially undermining the performance of the attack. To address the above significant shortcomings, we propose a non-intrusive graph distributed backdoor attack(NI-GDBA) that does not require backdoor triggers to be injected in the training data. Our attack trains an adaptive perturbation trigger generator model for each malicious client to learn the natural backdoor from the GNN model downloading from the server with the malicious client’s local data. In contrast to traditional distributed backdoor attacks on FedGL via trigger injection in training data, our attack on different datasets such as Molecules and Bioinformatics have higher attack success rate, stronger persistence and stealth, and has no negative impact on the performance of the global GNN model. We also explore the robustness of NI-GDBA under different defense strategies, and based on our extensive experimental studies, we show that our attack method is robust to current federated learning defense methods, thus it is necessary to consider non-intrusive distributed backdoor attacks on FedGL as a novel threat that requires custom d

关键词： Backdoor Attacks Federated Graph Learning

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Empowering Federated Graph Rationale Learning with Latent Environments 34

Empowering Federated Graph Rationale Learning with Latent En...

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34th ACM Web conference, WWW 2025

作者： Yue, Linan Liu, Qi Li, Yawen Yao, Fangzhou Gao, Weibo Du, Junping School of Computer Science and Engineering Southeast University Nanjing China State Key Laboratory of Cognitive Intelligence University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Cognitive Intelligence University of Science and Technology of China Hefei China

ISBN: (纸本)9798400712746

the success of Graph Neural networks (GNNs) in graph classification has heightened interest in explainable GNNs, particularly through graph rationalization. this method aims to enhance GNNs explainability by identifying subgraph structures (i.e., rationales) that support model predictions. However, existing methods often rely on centralized datasets, posing challenges in scenarios where data privacy is crucial, such as in molecular property prediction. Federated Learning (FL) offers a solution by enabling collaborative model training without sharing raw data. In this context, Federated Graph Rationalization emerges as a promising research direction. However, in each client, the rationalization methods often rely on client-specific shortcuts to compose rationales and make task predictions. Data heterogeneity, characterized by non-IID data across clients, exacerbates this problem, leading to poor prediction performance. To address these challenges, we propose the Environment-aware Data Augmentation (EaDA) method for Federated Graph Rationalization. EaDA comprises two main components: the Environment-aware Rationale Extraction (ERE) module and the local-Global Alignment (LGA) module. the ERE module employs prototype learning to infer and share abstract environment information across clients, which are then aggregated to form a global environment. this information is used to generate counterfactual samples for local clients, enhancing the robustness of task predictions. the LGA module uses contrastive learning methods to align local and global rationale representations, mitigating performance degradation due to data heterogeneity. Comprehensive experiments on benchmark datasets demonstrate the effectiveness of our approaches. © 2025 Copyright held by the owner/author(s).

关键词： Federated Learning Graph Rationale Learning

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A Witness System for Vehicular Ad Hoc networks

A Witness System for Vehicular Ad Hoc Networks

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ieee 34th conference on local computer networks

作者： Ali, Nasir Scheuermann, Bjoern Mauve, Martin Univ Dusseldorf Comp Networks Res Grp Dusseldorf Germany

ISBN: (纸本)9781424444885

Searching for witnesses in case of road accidents is a challenging task for the police and involved persons. In this paper, we propose a mechanism that helps to find witnesses. Our solution preserves the potential witnesses' anonymity and gives them a free hand to decide whether to step forward as a witness or not. We analyze the performance of our application using a realistic model of a German city.

关键词： Vehicular ad hoc networks

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Enhancements for ieee 802.11 networks with Directional Antennas

Enhancements for IEEE 802.11 Networks with Directional Anten...

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ieee 34th conference on local computer networks

作者： Nadeem, Tamer Siemens Corp Res Princeton NJ 08540 USA

ISBN: (纸本)9781424444885

Directional antennas have been introduced to improve the performance of 802.11 based wireless networks. Station equipped with directional antennas can beamform data in a specific direction. However, ieee 802.11 is developed with omni-directional antennas in mind. thus, deploying ieee 802.11 in a directional antenna environment leads stations to be conservative in blocking their own transmissions in favor of the ongoing transmissions. In this paper we propose two opportunistic enhancements for the ieee 802.11 networks using directional antennas. the first enhancement is to augment the 802.11 MAC protocol with additional information (i.e., location of the stations) that gives a node the flexibility to transmit data while there are ongoing transmissions in its vicinity. the second enhancement, using the augmented MAC protocol, alters the way the 802.11 accessing MAC data queue.

关键词： Wireless networks ieee 802.11 Medium Access Control Carrier Sense Directional Antenna Performance Analysis

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Defending Method Against Jamming Attack in Wireless Ad Hoc networks

Defending Method Against Jamming Attack in Wireless Ad Hoc N...

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ieee 34th conference on local computer networks

作者： Ben-Othman, Jalel Hamieh, Ali Univ Versailles CNRS PRiSM Lab F-78035 Versailles France

ISBN: (纸本)9781424444885

Mobile ad hoc networks (MANETs) are dynamic mobile networks that can be formed in the absence of any preexisting communication infrastructure. MANETs are vulnerable to jamming attack due to their salient characteristics. the objective of a jammer is to interfere with legitimate wireless communications, and to degrade the overall QoS of the network. In this paper, we propose a new method to react at jamming attacks. the military has long dealt with jamming by using frequency-hopping spread spectrum communication. Unlike frequency hopping that takes place at the PHY layer, our purpose takes place at the MAC layer.

关键词： Ad Hoc networks ieee 802.11 MAC Protocol Jamming Attack

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Neighbor Selection Techniques for Multi-Hop Wireless Mesh networks

Neighbor Selection Techniques for Multi-Hop Wireless Mesh Ne...

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ieee 34th conference on local computer networks

作者： Coll, Baldomero Gozalvez, Javier Univ Miguel Hernandez Elche Ubiquitous Wireless Commun Res Lab Elche 03202 Spain

ISBN: (纸本)9781424444885

Multi-hop wireless mesh networks, including Multi-Hop Cellular networks, base their operation on the establishment of multi-hop paths to route the information from source to destination. To this aim, it is crucial to define adequate neighbor selection techniques that choose the most appropriate nodes over which to route the information. In this context, this paper proposes a set of neighbor selection techniques that exploit spatial diversity to improve the performance and operation of multi-hop wireless mesh networks.

关键词： neighbor selection multi-hop communications mesh networking 802.11s multi-hop cellular networks

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A Route-Control Mechanism for Improving the Performance of Transport Protocols in a MANET

A Route-Control Mechanism for Improving the Performance of T...

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ieee 34th conference on local computer networks

作者： Cohen, Reuven Levin, Anna Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

ISBN: (纸本)9781424444885

We propose a new cross-layer mechanism, referred to as Route-control, for mobile ad-hoc networks (MANETs). this mechanism, which works in the Network and Transport layers, aims at enhancing the performance of MANETs' reliable Transport protocols. the main idea behind the proposed mechanism is to notify the sender when the packets of a Transport layer flow change their route. We show that the sender can benefit from this information when deciding whether to retransmit a missing segment or to wait, when estimating the RTT (Round Trip Time), and when deciding whether to change the congestion window.

关键词： Mobile ad hoc networks

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On the delay lower bound for the emergency message dissemination in vehicular ad-hoc networks

On the delay lower bound for the emergency message dissemina...

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ieee 34th conference on local computer networks

作者： Vinel, Alexey Koucheryavy, Yevgeni Russian Acad Sci St Petersburg Inst Informat & Automat St Petersburg 196140 Russia Tampere Univ Technol Dept Commun Engn Tampere Finland

ISBN: (纸本)9781424444885

Active safety in vehicular environment can be achieved by means of installation of the wireless equipment on the boards of cars. Design of highly efficient protocols for car-to-car communications is a challenging task. If an emergency situation happens on the road, the information about it should be disseminated to the stakeholders with low delay and high reliability. In this paper, we derive a theoretical lower bound for the mean message transmission delay in multi-hop vehicular ad-hoc networks.

关键词： Car-to-ear communications vehicular ad-hoc networks emergency messaging information dissemination analytical modeling

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