研究業績リスト
ジャーナル論文 - rm_published_papers: International Conference Proceedings
BITEX: A Cross-Layer Bandwidth Trading System for eXtended Reality Applications
公開済 20/05/2025
2025 IEEE 26th International Conference on High Performance Switching and Routing (HPSR), 1 - 7
ジャーナル論文 - rm_published_papers: International Conference Proceedings
DFTIMP: Distributed Fake Traffic Injection from Multiple Points for Obfuscation of IoT Traffic
公開済 11/01/2025
2025 IEEE International Conference on Consumer Electronics (ICCE), 1 - 4
ジャーナル論文 - rm_published_papers: Scientific Journal
Selective Early Congestion Signaling for QoE Fairness in ICN Video Streaming
公開済 2025
IEEE Access
ジャーナル論文 - rm_published_papers: Scientific Journal
公開済 2025
IEEE Access, 1 - 1
ジャーナル論文 - rm_published_papers: International Conference Proceedings
TCP Pacing Without Clock-Based Timing Control for Data Segment Transmission
公開済 13/12/2024
2024 10th International Conference on Computer and Communications (ICCC), 2495 - 2499
ジャーナル論文 - rm_published_papers: International Conference Proceedings
Preliminary Study of Data Augmentation for Video QoE Evaluation
公開済 09/07/2024
2024 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), 753 - 754
ジャーナル論文 - rm_published_papers: International Conference Proceedings
Experimental Study on The Effect of Time Synchronization Errors in VANET
公開済 09/07/2024
2024 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), 517 - 518
ジャーナル論文 - rm_published_papers: International Conference Proceedings
SRv6-based Route Shortening for Optimizing Communication Resources in Multi-homed Environments
公開済 09/07/2024
2024 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), 593 - 594
ジャーナル論文 - rm_published_papers: Scientific Journal
IDAC: Federated Learning-Based Intrusion Detection Using Autonomously Extracted Anomalies in IoT
公開済 18/05/2024
Sensors, 24, 10, 3218 - 3218
The recent rapid growth in Internet of Things (IoT) technologies is enriching our daily lives but significant information security risks in IoT fields have become apparent. In fact, there have been large-scale botnet attacks that exploit undiscovered vulnerabilities, known as zero-day attacks. Several intrusion detection methods based on network traffic monitoring have been proposed to address this issue. These methods employ federated learning to share learned attack information among multiple IoT networks, aiming to improve collective detection capabilities against attacks including zero-day attacks. Although their ability to detect zero-day attacks with high precision has been confirmed, challenges such as autonomous labeling of attacks from traffic information and attack information sharing between different device types still remain. To resolve the issues, this paper proposes IDAC, a novel intrusion detection method with autonomous attack candidate labeling and federated learning-based attack candidate sharing. The labeling of attack candidates in IDAC is executed using information autonomously extracted from traffic information, and the labeling can also be applied to zero-day attacks. The federated learning-based attack candidate sharing enables candidate aggregation from multiple networks, and it executes attack determination based on the aggregated similar candidates. Performance evaluations demonstrated that IDS with IDAC within networks based on attack candidates is feasible and achieved comparable detection performance against multiple attacks including zero-day attacks compared to the existing methods while suppressing false positives in the extraction of attack candidates. In addition, the sharing of autonomously extracted attack candidates from multiple networks improves both detection performance and the required time for attack detection.
ジャーナル論文 - rm_published_papers: International Conference Proceedings
Auto Annotation using Object Tracking with Multiple in-vehicle Cameras for Federated Learning
公開済 19/02/2024
2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)