A Zero-Shot Learning-Based Detection Model Against Zero-Day Attacks in IoT
Author:
Affiliation:
1. State Grid Smart Grid Research Institute co., Ltd,State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology,SGRI Power Grid Digitizing Technology Department,Beijing,China
Funder
National Key R&D Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10592861/10593657/10593684.pdf?arnumber=10593684
Reference19 articles.
1. IoT: Internet of Threats? A Survey of Practical Security Vulnerabilities in Real IoT Devices
2. Detecting zero-day attacks using context-aware anomaly detection at the application-layer
3. A Hybrid Real-time Zero-day Attack Detection and Analysis System
4. A framework for zero-day vulnerabilities detection and prioritization
5. Using Bayesian Networks for Probabilistic Identification of Zero-Day Attack Paths
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