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9th International Conference on Communications and Future Internet: ICCFI 2025 [Pehme köide]

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This book equips readers with cutting-edge research and practical solutions to thrive in the fast-evolving communications and future internet field. It compiles 15 rigorously reviewed papers from ICCFI 2025, offering actionable insights for academics and practitioners alike.



Organized by the University of the Ryukyus, this book captures innovations from ICCFI 2025 (July 1113, 2025, Okinawa, Japan). Topics span Trojan malware testing, UAV energy efficiency, AI-driven sentiment analysis, and blockchain securityblending engineering principles with real-world needs.



It bridges academia and industry, with case studies and interdisciplinary perspectives that turn theoretical concepts into deployable solutions. Essential for anyone shaping the future of communication technologies, this book reflects current trends while anticipating tomorrows challenges.
Simulating Trojan Malware Infections and Pirated Adobe Software: A
Penetration Testing and Vulnerability Testing using Triage.- Design and
Evaluation of the Proposed Road Reporting System for Cyclists.- TeeZKVCF:
TEE-based Zero-Knowledge Verifiable Credential Framework.- Effect of
Different Fading Channels in Spectrum Sensing for Cognitive Radio Based on
Machine Learning Using GLM Algorithm.- Flight Path Minimization for Energy
Efficiency in UAV-assisted Wireless Powered Communication Networks.-
Multi-variable Context-aware Offline-to-Online Reinforcement Learning
Framework for Autonomous IoT Devices.- Dual RIS-Assisted Monostatic L-Band
Radar Target Detection in NLoS Scenarios.- Blockchain Driven Security:
Protecting Data and Ensuring Trustworthiness in Federated Learning.-
Explainable AI for League of Legends game: Predicting Match Outcomes Through
In-game Data Analysis.- Deep Learning Based Text Mining on Global PBL
Description Data.- Model to Optimize Efficiency in MSG Purification Applying
IoT-Poka Yoke and AI-Automated Jidoka.- Boosting Expert Capabilities through
Contrastive Loss within a Mixture-of-Experts Framework for Continual
Learning.- Enhancing the Efficiency of Sentiment Analysis for Vietnamese
Hotel Reviews: A Deep Learning-Based Approach Combining Title and Content.- A
Study on Air Defense and Anti-Missile Battle System Modeling Based on
DoDAF-SysML.- Using Continual Learning for Real-Time Detection of Vulnerable
Road Users in Complex Traffic Scenarios.