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 distr...
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.
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...
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 conferencethat was part of the original conference proceedings.
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 secu...
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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 withthe 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
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 identifyi...
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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 wit...
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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.
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 dev...
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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.
Mobile ad hoc networks (MANETs) are dynamic mobile networksthat can be formed in the absence of any preexisting communication infrastructure. MANETs are vulnerable to jamming attack due to their salient characteristi...
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ISBN:
(纸本)9781424444885
Mobile ad hoc networks (MANETs) are dynamic mobile networksthat 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.
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 ...
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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.
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...
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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.
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...
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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.
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