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检索条件"丛书名=Computer Communications and Networks"

共 4934 条记录，以下是101-110 订阅

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RobustETH: Ensuring Economic Fairness in ETH2.0's Distributed Validator Technology 33

RobustETH: Ensuring Economic Fairness in ETH2.0's Distribute...

引用

33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Chen, Shenghang Xu, Zhicheng Zhou, Kun Zhang, Xiaoli Cheng, Hongbing Zhejiang Univ Technol Dept Comp Sci & Technol Hangzhou Peoples R China

ISBN: (纸本)9798350348439;9798350384611

Distributed Validator Technology (DVT) mitigates single points of failure in Ethereum validators by distributing validator duties across a node cluster and making decisions within the cluster through consensus algorithms. However, these systems often fail to ensure economic fairness for participants, where misconduct by a few nodes can lead to financial losses for honest nodes within the cluster. To address this issue, we introduce RobustETH, an innovative DVT implementation that prioritizes operational efficiency and economic fairness for participants. Specifically, RobustETH incorporates an efficient consensus protocol, X-IBFT, to enhance DVT's operational efficiency. Additionally, we propose a BFT forensic protocol and a reputation-based recluster strategy to accurately penalize malicious nodes and mitigate their impact, thereby safeguarding the financial interests of honest participants. Our theoretical analysis proves RobustETH's safety, liveness, and accountability. Moreover, through comprehensive evaluations, we demonstrate that RobustETH achieves a 58% reduction in end-to-end latency compared to current state-of-the-art DVT implementations while ensuring economic fairness.

关键词： Ethereum Distributed Validator Technology Byzantine faults tolerant

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Data Augmentation for Human Activity Recognition via Condition Space Interpolation within a Generative Model 33

Data Augmentation for Human Activity Recognition via Conditi...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Wang, Tianshi Chen, Yizhuo Yang, Qikai Sun, Dachun Wang, Ruijie Li, Jinyang Kimura, Tomoyoshi Abdelzaher, Tarek Univ Illinois Dept Comp Sci Urbana IL 61801 USA

ISBN: (纸本)9798350348439;9798350384611

This paper presents a generative data augmentation approach for human activity recognition (HAR) to close the distribution gap between laboratory training and real-world deployment. Despite the recent success of deep learning methods in wearable sensor-based HAR tasks, performance degradation occurs during real-world deployment due to training data scarcity and the vast variability in human activities. In light of this, we aim to enhance the diversity of training datasets by generating new data points within the vicinity of existing samples, as informed by domain expertise. Unlike the commonly utilized methods that augment data by interpolating in data space or feature space, we innovate by applying interpolation in the condition space of a conditional generative model to augment HAR datasets. We use domain-specific knowledge to extract statistical metrics from sensor data, which serve as conditions to direct the generation process. We demonstrate how a conditional generative diffusion model, steered by interpolated conditions, can synthesize realistic new data with various high-level features that benefit the robustness of the downstream HAR models. Our methodology advances the use of interpolation in data augmentation by exploring the capability of a state-of-the-art generative model, offering novel perspectives for bolstering the robustness and generalizability of HAR systems. Experimental results demonstrate that condition space interpolation outperforms the conventional interpolation-based and generative model-based augmentation methods across various datasets and downstream classifier combinations.

关键词： human activity recognition data augmentation generative model diffusion model

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Foundations of In-Network Quantum Computing for Future Communication networks 33

Foundations of In-Network Quantum Computing for Future Commu...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Boeck, Yannik Boche, Holger Bassoli, Riccardo Fitzek, Frank H. P. Tech Univ Munich Chair Theoret Informat Technol D-80333 Munich Germany Munich Ctr Quantum Sci & Technol MCQST Munich Germany MQV Munich Germany Tech Univ Dresden CeTI Deutsch Telekom Chair Commun Networks Dresden Germany Tech Univ Dresden BMBF Res Hub 6G Life TU Dresden Dresden Germany

ISBN: (纸本)9798350348439;9798350384611

In-Network Computing has brought computing and communication together at every communication node in the digital world, this work lays the foundations for doing the same in the quantum world, improving communication properties in the process - a combination of quantum computing and quantum communication. Full network softwarization, in-network intelligence, and massive connectivity will create an unprecedented demand for computing resources in the digital world. Accordingly, the scientific and industrial communities have begun to explore technologies such as quantum computing and have made significant efforts to demonstrate an algorithmic advantage for various problems. However, practical quantum computers are resource-inefficient and difficult to build. This article introduces a new communication paradigm leading to the concept of quantum in-network computing in the context of entanglement-assisted communication and computing for inherent distributed resilience and sensing. We review the fundamentals of digital hardware as characterized by Turing's computability theory and demonstrate their relevance to mathematically rigorous characterizations of gate-based quantum computing. We then provide such a characterization using methods from effective analysis, leading to significant results that reveal the inherent theoretical limitations of universal gate-based quantum computers. These results support our assessment that gate-based quantum in-network computing is only possible through specialized, non-universal solutions that are seamlessly integrated with high-performance digital computing.

关键词： In-network quantum computing universal quantum computing Turing machines network as a sensor entanglement-assisted communications network resilience

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RecuGAN: A Novel Generative AI Approach for Synthesizing RF Coverage Maps 33

RecuGAN: A Novel Generative AI Approach for Synthesizing RF ...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Sarkar, Sopan Manshaei, Mohammad Hossein Krunz, Marwan Ravaeet, Hamid Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran

ISBN: (纸本)9798350348439;9798350384611

Radio-frequency coverage maps (RF maps) are essential in wireless communication, but obtaining them through site surveys can be labor-intensive and sometimes impractical. To address this challenge, we propose RecuGAN, a generative adversarial network (GAN)-based approach for generating RF maps. RecuGAN leverages the principles of information maximizing GAN (InfoGAN) to capture latent properties of RF maps, enabling unsupervised categorization and generation of new and diverse RF maps. Unlike traditional methods, RecuGAN does not require labeled data or conditional input, reducing complexity, time, and cost. We enhance the RecuGAN objective function with a customized gradient penalty-based Wasserstein GAN (WGAN) function and a gradient-based loss function for stable training and accurate map generation. We also provide the option to incorporate multiple generators in RecuGAN, enabling high-resolution RF map generation. As demonstrated through extensive training with both experimental and simulation data, RecuGAN can synthesize diverse high-quality RF maps and categorize them based on the RSS distribution. Compared to a UNet-based conditional GAN (cGAN), RecuGAN achieves a mean average percentage error (MAPE) of 1.18%, outperforming the cGAN model, which achieves a MAPE of 2.5%.

关键词： Generative Adversarial networks RF Mapping Deep Neural networks Coverage AI

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Predicting F1-Scores of Classifiers in Network Intrusion Detection Systems 33

Predicting F1-Scores of Classifiers in Network Intrusion Det...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Silva, Priscila Baye, Gaspard Broggi, Alexandre Bastian, Nathaniel D. Kul, Gokhan Fiondella, Lance Univ Massachusetts Dartmouth Elect & Comp Engn Dartmouth MA 02747 USA Univ Massachusetts Dartmouth Comp & Informat Sci Dartmouth MA USA US Mil Acad Army Cyber Inst West Point NY 10996 USA

ISBN: (纸本)9798350348439;9798350384611

With the evolution of the Internet of Things, network intrusion detection systems (NIDS) are vital for protecting networks by monitoring and analyzing network traffic to detect potential cyber threats. Deep neural networks (DNNs) are widely used in NIDS for their accurate classification and response capabilities against threats. However, there is a lack of detailed discussion in the literature about evaluating DNN performance in real-time scenarios for monitoring and assurance of NIDS. This paper fills this gap by applying multiple linear regression models to predict the F1-score of a DNN attack classifier. The predictive models are evaluated using a pre-trained DNN on a NIDS benchmark dataset, where three different distance metrics computed between real-time instances and known attack patterns stored in historical data are considered as model covariates. Our findings show that the multiple linear regression model with interaction between covariates confidently forecasts the F1-score for future periods, demonstrating its ability to anticipate future observations with an empirical coverage of 94.4%.

关键词： Network intrusion detection systems deep neural networks multiple linear regression covariates

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Eavesdropper-Avoiding Neighbor Discovery for Multi-Sector Directional Wireless Systems 33

Eavesdropper-Avoiding Neighbor Discovery for Multi-Sector Di...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Sarder, Md Asif Ishrak Yuksel, Murat Bentley, Elizabeth Univ Cent Florida Orlando FL 32816 USA Air Force Res Lab Rome NY USA MIT Lincoln Lab 244 Wood St Lexington MA 02173 USA

ISBN: (纸本)9798350348439;9798350384611

Directional antenna systems are gaining widespread adoption in wireless communication solutions, particularly using super-6 GHz bands in the electromagnetic spectrum. Hence, neighbor discovery and beam alignment in these directional wireless systems have attracted notable attention from researchers. However, fast neighbor discovery using directional wireless while maintaining covertness from eavesdroppers by minimizing the probability-of-intercept (POI) is an open research problem. We address this trade-off by proposing a sequential transceiver (or direction) selection protocol based on a tuning parameter (alpha) that guides the nodes to prioritize either goal by selecting the next operational transceiver subset for probing. We consider a 2-D multi-sector directional wireless system with electronic steering of transmission among sectors, assuming each sector is equipped with a transceiver and the sectors collectively cover the 2-D 360 degrees horizon around the node. We design a time-slotted neighbor discovery protocol that employs a probabilistic approach to select only one transceiver to use for the next time interval. By changing alpha, we study its capability to control the probing direction and impact on neighbor discovery speed and POI. Results show random selection offers fastest neighbor discovery but increases vulnerability to passive eavesdropping. Choosing from transceivers placed opposite to the active one accelerates discovery, while prioritizing the adjacent ones enhances covertness. During the search for the best alpha, we observe that exclusively prioritizing either rapid discovery or minimizing POI for a long stretch does not yield an optimal solution.

关键词： Neighbor Discovery Probability-of-Intercept Directional Wireless Super-6 GHz

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LEMUR: Efficient Multicasting in Ad-hoc networks Using Label Switching and Unicast Routing 33

LEMUR: Efficient Multicasting in Ad-hoc Networks Using Label...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Cirimelli-Low, Dylan Garcia-Luna-Aceves, J. J. Univ Calif Santa Cruz Comp Sci & Engn Dept Santa Cruz CA 95064 USA Univ Toronto Dept Elect & Comp Engn Toronto ON Canada

ISBN: (纸本)9798350348439;9798350384611

To avoid forwarding loops and the transmission of unwanted replicas of multicast data packets, current multicast routing protocols designed for ad-hoc networks require routers to use packet caches listing enough information about multicast data packets that have been forwarded. In addition, existing multicast-routing solutions for ad-hoc networks either require a multicast routing protocol that operates concurrently with a unicast routing protocol, or adding substantial signaling to the baseline unicast routing protocol. We introduce a new approach for multicasting embedded in unicast routing that eliminates the need to use packet caches for multicasting along shared multicast trees by means of label switching, and incurs minimum additional signaling overhead to attain multicast routing.

关键词： Routing multicast ad-hoc networks

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Channel Estimation for MIMO-OTFS Satellite Communication: a Deep Learning-Based Approach 33

Channel Estimation for MIMO-OTFS Satellite Communication: a ...

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Gao, Yuan Xu, Xinchen Hu, Bintao Du, Jianbo Yang, Wenrui Jin, Yanliang Shanghai Univ Shanghai Peoples R China Xian Jiaotong Liverpool Univ Xian Peoples R China Xian Univ Posts & Telecommun Xian Peoples R China CTTIC Smart Data Co Ltd Hong Kong Peoples R China

ISBN: (纸本)9798350348439;9798350384611

The orthogonal time frequency space (OTFS) modulation has garnered significant attention due to its potential to combat the frequency Doppler effect in high-mobility scenarios, especially in the low earth orbit (LEO) satellite communication. However, facilitating the OTFS in multiple-input and multiple-output (MIMO) satellite communication requires accurate channel state information, which is a challenging task. To this end, we propose a novel deep-learning-based framework to enhance the channel estimation accuracy in a MIMO satellite communication network by exploiting the channel correlation of the OTFS-MIMO channels. Through extensive simulations, our proposed framework shows an impressive capability to predict MIMO-OTFS channels with remarkable accuracy enhancement. The effect of dataset and data distribution on the channel estimation accuracy and generalization are also revealed.

关键词： OTFS LEO MIMO Channel Estimation Deep Learning

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Digital Twin based Internet of Vehicles 33

Digital Twin based Internet of Vehicles

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Qian, Cheng Qian, Mian Hua, Kun Liang, Hengshuo Xu, Guobin Yu, Wei Hood Coll Dept Comp & Informat Technol Frederick MD 21701 USA Towson Univ Dept Comp & Informat Sci Towson MD 21252 USA Calif Polytech State Univ San Luis Obispo Dept Elect Engn San Luis Obispo CA 93407 USA Morgan State Univ Dept Comp Sci Baltimore MD 21251 USA

ISBN: (纸本)9798350348439;9798350384611

The Internet of Vehicles (IoV), as one subset of the Internet of Things (IoT) in the smart transportation area, integrates vehicle networks with sensors and actuators. By connecting all sensors to the network, the IoV enables smart transportation (i.e., autonomous vehicles) and makes smart cities a reality. In smart transportation systems, roadside units (RSUs) capture all vehicle information and serve as gateways. However, smart transportation infrastructure has yet to mature in the current stage. RSUs are insufficient to support all vehicles. Meanwhile, the low computational capability of vehicles makes it challenging to recompute the driving route as the road environment changes. To address the problem of insufficient RSU coverage, one protocol called IEEE 802.11p enables vehicle-to-vehicle communication using relays. Nonetheless, data transfer among vehicles via relays is still time-consuming for a large-scale transportation network. To deal with the above issues, in this paper, we propose an IoV framework using digital twins (DTs) to digitize the IoV environment and assign nearby IoT gateways compatible with the RSU communication protocol. This framework lets DTs update the vehicle's driving route based on real-time information. With a case study, we evaluate the efficacy of DT-assisted IoV based on communication latency and vehicle driving efficiency. Our evaluation results confirm that the proposed framework can efficiently enhance communication latency when the relay needs to pass through two or more vehicles and reduce travel time when vehicles receive updated route information at intersections.

关键词： Internet of Vehicles Digital Twin Publish subscription CoAP

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Location Privacy Protection Method with Route Constraints 33

Location Privacy Protection Method with Route Constraints

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33rd IEEE International Conference on computer communications and networks (ICCCN)

作者： Han, Jiang Xian, Hequn Yang, Dalin Jiang, Han Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Inst Software Trusted Comp & Informat Assurance Lab Beijing Peoples R China Qingdao Univ Qingdao Peoples R China Cryptog & Cyberspace Secur Whampoa Acad Guangzhou Peoples R China Washington Univ Sch Med St Louis MO USA

ISBN: (纸本)9798350348439;9798350384611

A location privacy protection method based on route constraints is proposed for the use of location-based services in vehicular networks. This scheme proposes a system architecture based on semi trusted third-party services, which stores user private information separately on three parties. Even if attackers acquire some information, they still cannot obtain the complete private information of the user, thus effective resists single point attacks from attackers. In addition, a dummy location selection algorithm based on route constraints and query history is proposed, which improves the privacy protection by maximizing physical dispersion, and location difference. The proposed method does not require any reliable third-party server, which can protect vehicle location privacy against inference attacks using route information, service record, and other auxiliary information. Security and cost analysis was conducted on the proposed method. The experimental results showed that this method can ensure the uncertainty and physical dispersion of dummy locations, improving the effectiveness of dummy locations, and effectively protect vehicle location privacy.

关键词： location privacy vehicular networks dummy location location-based services

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