An Empirical Evaluation of the Usefulness of Word Embedding Techniques in Deep Learning-Based Vulnerability Prediction
Gespeichert in:
| Veröffentlicht in: | EuroCybersec (2. : 2021 : Nizza) Security in computer and information sciences |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
2022
|
| Schlagworte: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen | Titel | Jahr | Verfasser |
|---|---|---|
| Correlation-Based Anomaly Detection for the CAN Bus | 2022 | Gazdag, András |
| AI and Quality of Service Driven Attack Detection, Mitigation and Energy Optimization: A Review of Some EU Project Results | 2022 | Çağlayan, Mehmet Ufuk |
| Botnet Attack Detection with Incremental Online Learning | 2022 | Nakip, Mert |
| Optimizing Energy Usage for an Electric Drone | 2022 | Czachórski, Tadeusz |
| Secure Authentication for Everyone! Enabling 2nd-Factor Authentication Under Real-World Constraints | 2022 | Fietkau, Julian |
| Application of a Human-Centric Approach in Security by Design for IoT Architecture Development | 2022 | Vasileva, Violeta |
| Mitigating the Massive Access Problem in the Internet of Things | 2022 | Gelenbe, Erol |
| T-RAID: TEE-based Remote Attestation for IoT Devices | 2022 | Nagy, Roland |
| An Empirical Evaluation of the Usefulness of Word Embedding Techniques in Deep Learning-Based Vulnerability Prediction | 2022 | Kalouptsoglou, Ilias |
| Energy, QoS and Security Aware Edge Services | 2022 | Gelenbe, Erol |