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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Dong-Seong Kim

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5 papers indexed here

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Conference Aug 2026

DASF-Net: A Despeckling-Attentive SAR-Optical Fusion Network for Coastal Land Cover Mapping

Rapid and often unplanned growth along India's coast makes timely land-use and land-cover (LULC) monitoring essential, yet the optical satellite imagery normally used for this task is frequently obscured by cloud during the monsoon over cities such as Mumbai. Synthetic Aperture Radar (SAR) acquires data throughout the...

H. Singh, Ashish Kumar Tripathi, Manthan Deshmukh et al. · 0 citations
Conference Aug 2026

FedCWD: Confidence-Weighted Federated Knowledge Distillation for Heterogeneous IoT Edge Devices

Federated learning (FL) over heterogeneous IoT devices is hindered by two practical constraints: standard weightaveraging methods such as FedAvg require homogeneous model architectures across clients, and distillation-based alternatives such as FedDF depend on a labelled proxy dataset at the server. In this paper, we p...

M. Putra, I. G. J. E. Putra, Gabriel Avelino R. Sampedro et al. · 0 citations
Conference Aug 2026

FedPurge: Byzantine-Robust Federated Aggregation via Cosine Filtering and Trusted-Subset Median for 6G Edge Intrusion Detection

Federated learning (FL) offers a compelling framework for collaborative intrusion detection across distributed 6G edge nodes without centralizing sensitive network traffic data. However, existing aggregation strategies remain vulnerable to poisoning attacks, particularly when malicious clients constitute a large fracti...

M. Putra, N. Karna, I. G. J. E. Putra et al. · 0 citations
Conference Aug 2026

Calibration Collapse in Federated Industrial IoT Intrusion Detection Under Non-IID Heterogeneity

Federated learning (FL) has been proposed for privacy-preserving Industrial Internet of Things (IIoT) intrusion detection, and predictive uncertainty is expected to support zeroday attack recognition. We compare centralized learning with FedAvg, Mean, Trimmed Mean, Krum, and DP-FedAvg on nearindependent and identically...

C. I. Nwakanma, V. Ihekoronye, Love Allen Chijioke Ahakonye et al. · 0 citations
Conference Aug 2026

Towards Secure Blockchain-Based E-Wallets: A Performance and Security Evaluation

Blockchain-based e-wallet systems offer stronger auditability and tamper resistance than fully centralized architectures; however, the choice of consensus mechanism directly affects transaction performance. This paper presents a blockchain-based e-wallet application that employs AES and RSA to secure transaction data b...

Daffa Ilham Pramadhan, Ahmad Zainudin, Amang Sudarsono et al. · 0 citations

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