专题：Internet Traffic Analysis and Secure E-voting

This cluster of papers focuses on the application of machine learning and deep learning techniques for the classification and analysis of internet traffic, including encrypted traffic, network behavior, and IoT device identification. It also covers topics related to anonymity, traffic analysis, and electronic voting.
最新文献
FreightBox Zero: Three-Layer Agent Safety Stack — Hard Gate, Five Locks, and Kernel Receipts for AI-Operated NVOCCs (v3)

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[SUPERSEDED → DOI: 10.5281/zenodo.19512987 (v2.0)] CALL FOR PAPERS: The Distributed Journal as Counter-Infrastructure v1.0 — Initial Draft (Crimson Hexagonal Archive)

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Smart grid false data injection detection through federated learning with deep learning models

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Boosted Ensemble Voting for Intrusion Detection: A SHAP-Driven Analysis of XGBoost and CatBoost

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Detection of dummy data injection attacks by using particle swarm optimization-attention temporal graph convolutional network model in power system

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Attention-enhanced BiLSTM-ANN framework with CNN-based feature selection for advanced threat detection

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Secure IoT Data Aggregation using Lightweight Homomorphic Encryption and Trust Modeling with Fingerprint Verification

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A Survey of Supervised, Unsupervised, and Ensemble Learning Approaches for DDoS Detection in SDN

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A Format-Verifiable E-Voting Scheme Using Homomorphic Encryption

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CNN-LSTM Powered Network IDS for Adaptive Cyber Defence

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近5年高被引文献
Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning

article Full Text OpenAlex 883 FWCI113.8558

CICIoT2023: A Real-Time Dataset and Benchmark for Large-Scale Attacks in IoT Environment

article Full Text OpenAlex 749 FWCI145.2969

A survey on federated learning: challenges and applications

article Full Text OpenAlex 712 FWCI85.507

Heterogeneous Federated Learning: State-of-the-art and Research Challenges

review Full Text OpenAlex 476 FWCI79.6479

Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges

article Full Text OpenAlex 476 FWCI79.8226

Recent Advances on Federated Learning for Cybersecurity and Cybersecurity for Federated Learning for Internet of Things

article Full Text OpenAlex 440 FWCI58.1588

ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification

article Full Text OpenAlex 425 FWCI38.6626

Anomaly-based intrusion detection system for IoT networks through deep learning model

article Full Text OpenAlex 399 FWCI54.1761

Federated Learning for intrusion detection system: Concepts, challenges and future directions

article Full Text OpenAlex 394 FWCI49.4253

Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities

article Full Text OpenAlex 358 FWCI46.6429