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

共 4934 条记录，以下是41-50 订阅

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Hybrid LoRa Network Architecture: Automatic Switching between LoRaWAN and LoRa Mesh Network in Environments with Dynamic Obstacle Variations 33

Hybrid LoRa Network Architecture: Automatic Switching betwee...

引用

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

作者： Kim, Hyungsub Kim, Hayoung Baek, Somi Melenchuk, Ryan Soroka, Jaden Smith, Anthony Sangmyung Univ Software Engn Cheonan South Korea Soongsil Univ Sch Software Seoul South Korea Kyonggi Univ Comp Engn Suwon South Korea Purdue Univ Comp & Informat Technol W Lafayette IN 47907 USA

ISBN: (纸本)9798350348439;9798350384611

The LoRaWAN network is widely employed in agricultural Internet of Things (IoT) applications requiring long-range wireless communication and low-energy consumption. However, challenges arise in dynamic environments like woodlands, where obstacles such as tree foliage disrupt the Fresnel zone and absorb signals. A previous study proposes a solution utilizing a LoRa Mesh Network (LoRa Meshnet) capable of establishing connections under tree canopies. Still, LoRa Meshnet is less battery-efficient than LoRaWAN. Thus, relying solely on LoRa Meshnet is inefficient in situations where LoRaWAN communication is affected by dynamic obstacles like seasonally varying foliage. To address this, we introduce a hybrid LoRa network architecture that utilizes LoRaWAN as the primary network and LoRa Meshnet as the backup, automatically switching between them. This approach ensures energy efficiency in sparse foliage situations by using LoRaWAN while guaranteeing stable data transmission in dense foliage scenarios with the use of LoRa Meshnet. Additionally, the system offers easy network deployment and cost-effectiveness.

关键词： Internet of Things LoRa LoRaWAN LoRa Mesh Network Hybrid Architecture

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FL-EVCS: Federated Learning based Anomaly Detection for EV Charging Ecosystem 33

FL-EVCS: Federated Learning based Anomaly Detection for EV C...

引用

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

作者： Purohit, Shaurya Govindarasu, Manimaran Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

ISBN: (纸本)9798350348439;9798350384611

The rapid expansion of electric vehicle (EV) technologies and their seamless integration into smart grids herald a significant transition toward sustainable energy practices, highlighting the need to bolster Electric Vehicle Charging Stations (EVCS). These stations, connected through protocols like ISO 15118 and OCPP, ensure secure interactions between EVs, EVCS, and management systems. However, the rise of Internet of Things (IoT) connectivity exposes EVCS to cyber threats, including Distributed Denial of Service (DDoS), Man-in-the-Middle (MitM), and Injection attacks, which threaten the stability of thousands of EVCS and the overall charging infrastructure. In response to these challenges, this paper presents a Federated Learning-based Anomaly Detection System (FL-EVCS), an approach that significantly enhances the cybersecurity framework within EVCS networks. By adopting a federated learning model, FL-EVCS prioritizes data privacy by exchanging model parameters instead of raw data across the network. This method offers a powerful collective defense strategy, considerably enhancing the capabilities of traditional ADS that utilize machine learning algorithms such as KNN, RF, and SVM. In our evaluations, FL-EVCS demonstrated good performance by achieving an accuracy of around 97% and superior F1-scores, compared to traditional ML-based ADS using the CICEVSE2024 dataset. By enhancing EVCS security against cyber threats and supporting EV market growth with a secure user-friendly infrastructure, FL-EVCS markedly increases detection accuracy and efficiency. This approach offers a well-balanced solution for anomaly detection, meeting stringent data privacy requirements and promoting the resilience and expansion of the EVCS ecosystem.

关键词： EVCS IoT Federated learning Anomaly detection Cybersecurity

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Unlocking Efficiency in B5G networks: The Need for Adaptive Service Function Chains 33

Unlocking Efficiency in B5G Networks: The Need for Adaptive ...

引用

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

作者： Abreu, David Perez Velasquez, Karima Curado, Marilia Monteiro, Edmundo Inst Pedro Nunes Lab Informat & Syst Coimbra Portugal Univ Coimbra Dept Informat Engn CISUC Coimbra Portugal

ISBN: (纸本)9798350348439;9798350384611

Service Function Chains allow the dynamic generation of basic virtual network services in order to build more complex services. They constitute the basis of the flexibility support for 5G and Beyond 5G networks. In order to totally exploit their benefits, the Service Function Chains should adapt to specific user requirements and current network status. The existing mechanisms to compose and embed Service Function Chains mostly disregard energy metrics to guide their decisions, thus resulting in a lack of energy optimisation by network operators. This paper presents a revision of existing Service Function Chain composition and embedding approaches and a discussion of current and future research directions, focused on energy optimisation for adaptive Service Function Chains. Furthermore, an architecture to empower the green orchestration of adaptive Service Function Chains is also drafted.

关键词： Service Function Chain Adaptive SFC B5G Energy Efficiency Green Orchestration

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Beyond Wake Words: Advancing Smart Speaker Protection with Continuous Authentication and Local Profiles 33

Beyond Wake Words: Advancing Smart Speaker Protection with C...

引用

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

作者： Acosta, Luca Hernandez Reinhardt, Andreas Mueller, Tobias Reinhardt, Delphine Univ Gottingen Inst Comp Sci Comp Secur & Privacy CSP Gottingen Germany Tech Univ Clausthal Dept Informat Clausthal Zellerfeld Germany

ISBN: (纸本)9798350348439;9798350384611

Voice assistants, as provided by smart speakers, have become ubiquitous. Current authentication methods in these systems, however, rely on wake words, posing a risk due to the susceptibility to replay attacks. Additionally, user data stored on servers could expose sensitive information. This study suggests an approach to improve user authentication and profile management in smart speakers, reducing risks tied to external data processing and storage. We propose a two-fold solution for continuous user authentication and local user profiles. This approach prevents unauthorized access to sensitive data and grants users access to their local recordings. Our method differs from current practices in two ways: (1) It authenticates users based on complete voice commands, reducing the risk of replayed wake word attacks, and (2) it operates locally, avoiding the transfer of sensitive data to external servers. We offer a proof-of-concept with Alexa Voice Service (AVS) integration and a thorough evaluation using voice datasets and a study with 17 participants. We tested our approach under various conditions, including accents, background noise, and muffled speech. Legitimate users are identified with 93% precision, 95% recall, 94% F1-score, and 99% accuracy, while illegitimate users are recognized with 99% accuracy across these metrics.

关键词： smart speakers voice assistants voice authentication replay attacks local profiles privacy

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Scaling Container Caching to Larger networks with Multi-Agent Reinforcement Learning 33

Scaling Container Caching to Larger Networks with Multi-Agen...

引用

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

作者： Chen, Austin Ishigaki, Genya San Jose State Univ Dept Comp Sci San Jose CA 95192 USA

ISBN: (纸本)9798350348439;9798350384611

The development of containers as a tool for scalable computing has led to the increased use of the serverless edge computing paradigm. In particular, containers enable fast deployment of services to edge networks, allowing users to access spatially closer servers and resulting in lower latency. As instantiating containers can cause extra delay called a cold start delay, container caching, which keeps used containers alive in memory for reuse by the next user, has been proposed to mitigate the delay. However, such edge servers are constrained in their memory capacity, and there is a need for an efficient caching strategy. In this paper, we demonstrate that Multi-Agent Reinforcement Learning (MARL) can effectively learn a cache replacement policy and outperform traditional heuristic and centralized Deep Reinforcement Learning (DRL) algorithms. Our results also show that the proposed MARL's smaller action space has a significant advantage over DRL, which requires full information about the network. In particular, our research demonstrates that MARL is able to scale to larger networks without significant sacrifices to performance.

关键词： Serverless Edge Computing (SEC) Container Caching Multi-Agent Reinforcement Learning

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Digital Twin Continuum: a Key Enabler for Pervasive Cyber-Physical Environments 33

Digital Twin Continuum: a Key Enabler for Pervasive Cyber-Ph...

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

作者： Barbone, Antonello Burattini, Samuele Martinelli, Matteo Picone, Marco Ricci, Alessandro Virdis, Antonio Univ Modena & Reggio Emilia Modena Italy Univ Pisa Pisa Italy Univ Bologna Campus Cesena Cesena Italy

ISBN: (纸本)9798350348439;9798350384611

The rise of Digital Twin (DT) technology has revolutionized various sectors, offering simulation, monitoring, and optimization capabilities for complex systems. However, the rapid expansion of DT platforms, coupled with the need to deploy twins across the edge-to-cloud computing spectrum, has led to significant fragmentation and management challenges. These complexities should not hinder the application layer's goal of achieving interoperability and integrated management of DT instances. This paper introduces the Digital Twin Continuum (DTC) as a unified framework to address the challenges of DT coordination, hiding platform intricacies, while tackling the orchestration of communication and computing resources in the edge-to-cloud continuum. In this study, we define the concept of DTC, outlining its modeling principles, core functionalities and architectural components. We conduct an initial experimental evaluation of a DTC prototype in a realistic automotive use case, targeting two reference DT runtimes.

关键词： Digital Twin Compute-Continuum Cyber-Physical Systems

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CoWiL: Combating Cross-Technology Interference in LoRaWAN 33

CoWiL: Combating Cross-Technology Interference in LoRaWAN

引用

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

作者： Shao, Chenglong Tsukamoto, Kazuya Mat, Yi-Wei Huat, Yingbo Wan, Xianpeng Kyushu Inst Technol Iizuka Fukuoka Japan Natl Taiwan Univ Sci & Technol Taipei Taiwan Univ Calif Riverside Riverside CA 92521 USA Hainan Univ Haikou Hainan Peoples R China

ISBN: (纸本)9798350348439;9798350384611

Long-range wide area network (LoRaWAN) has been newly designed to exploit the 2.4 GHz unlicensed band instead of the traditional sub-GHz bands. However, this makes LoRaWAN frequently suffer from wireless communication failures caused by the cross-technology interference (CTI) from coexisting Wi-Fi networks using the same 2.4 GHz band. As a physical-layer solution to this problem, this paper presents CoWiL to combat the CTI from Wi-Fi to LoRa (the physical layer of LoRaWAN) in the 2.4 GHz band for better coexistence between LoRaWAN and Wi-Fi networks. Existing approaches address this problem by sacrificing Wi-Fi transmission performance or assuming that Wi-Fi interferes with only a small portion of LoRa signals. Unlike them, CoWiL does not affect normal Wi-Fi communications and is workable regardless of the degree of the CTI. This is achieved by implementing CoWiL at a LoRa receiver to directly extract LoRa data out of the CTI from Wi-Fi. Specifically, CoWiL exploits the correlation of the signal demodulation results between the preamble and the payload of a LoRa signal. A novel frequency bin mask is generated based on the demodulated preamble and then applied to the following payload for data decoding. Experimental results in various real-world environments show that in comparison with the existing solutions, CoWiL can reduce the packet error rate of LoRa transmissions by up to 96% under the CTI from Wi-Fi.

关键词： LoRaWAN LoRa Wi-Fi cross-technology interference coexistence physical layer

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KESIC: Kerberos Extensions for Smart, IoT and CPS Devices 33

KESIC: Kerberos Extensions for Smart, IoT and CPS Devices

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

作者： Tarafder, Renascence Jakkamsetti, Sashidhar Tsudik, Gene Univ Calif Irvine Irvine CA 92717 USA Bosch Res Sunnyvale CA USA

ISBN: (纸本)9798350348439;9798350384611

Secure and efficient multi-user access mechanisms are increasingly important for the growing number of Internet of Things (IoT) devices being used today. Kerberos is a well-known and time-tried security authentication and access control system for distributed systems wherein many users securely access various distributed services. Traditionally, these services are software applications or devices, such as printers. However, Kerberos is not directly suitable for IoT devices due to its relatively heavy-weight protocols and the resource-constrained nature of the devices. This paper presents KESIC, a system that enables efficient and secure multi-user access for IoT devices. KESIC aims to facilitate mutual authentication of IoT devices and users via Kerberos without modifying the latter's protocols. To facilitate that, KESIC includes a special Kerberized service, called IoT Server, that manages access to IoT devices. KESIC presents two protocols for secure and comprehensive multi-user access system for two types of IoT devices: general and severely power constrained. In terms of performance, KESIC consumes approximate to 47 times less memory, and incurs approximate to 135 times lower run-time overhead than Kerberos.

关键词： Application programs

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A Distortion Free Watermark Scheme for Relational Databases 33

A Distortion Free Watermark Scheme for Relational Databases

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

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

ISBN: (纸本)9798350348439;9798350384611

Database watermark is an effective solution to the piracy and data leakage problems. It is recognized as the final defense line in zero-trust architecture. Most of the traditional watermark schemes are based on carrier modification, which is difficult to achieve robustness while maintaining data quality. A new distortion free relational data watermark scheme is proposed, which guarantees data quality. Firstly, a watermark encoding algorithm is applied to combine bits in the data with the watermark information to generate auxiliary data, which is then stored. In the watermark extraction stage, the watermark decoding algorithm extracts the watermark information from the auxiliary data. The watermark capacity is greatly increased by encoding at least one attribute of each tuple. This does not modify the original data in any way and avoids the data distortion problems associated with traditional schemes. The experimental results show that the proposed scheme is more robust than traditional robust watermark schemes.

关键词： relational data watermark distortion free robust watermark

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Web3.0 Literary Landscape: Deep Learning and Blockchain for Nobel Prize Predictions 33

Web3.0 Literary Landscape: Deep Learning and Blockchain for ...

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

作者： Huang, Sida Tan, Jialuoyi Dong, Yuji Zhang, Jie Xian Jiaotong Liverpool Univ Sch Internet Things Suzhou Peoples R China Xian Jiaotong Liverpool Univ Sch Intelligent Finance & Business Suzhou Peoples R China Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou Peoples R China

ISBN: (纸本)9798350348439;9798350384611

This research introduces a cutting-edge Web3 literary analysis platform, harnessing the power of blockchain and deep learning technologies. By employing the immutable and transparent nature of blockchain, the platform ensures robust copyright protection while offering readers enhanced interactive features. It applies deep learning techniques for comprehensive analyses of sentiment, topic, and stylistic elements, which are instrumental in predicting potential Nobel Prize laureates. This methodology not only enhances the accuracy of predictions but also sheds light on the evaluation criteria and historical trends associated with the Nobel Prize. Moreover, the platform adopts a directed graph model alongside the struc2vec algorithm to create text vectors for comparative studies, uncovering similarities between works that have won awards and those that have been nominated. Utilizing the LESS model for detailed content examination, the platform delves into sequence relationships within semantic networks, thus improving interpretability and visualization. The integration of blockchain technology guarantees access to unbiased datasets, enabling more precise literary analyses and predictions. This innovative approach has been validated using works that have either won or been nominated for the Nobel Prize, proving its efficacy in identifying the textual characteristics favored by the Nobel Prize committee.

关键词： Web 3.0 Blockchain Semantic analysis Deep learning struc2vec Sequence mining

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