[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
A comprehensive survey on the security of smart grid: Challenges, mitigations, and future research opportunities
A Zibaeirad, F Koleini, S Bi, T Hou, T Wang - ar** the digital epoch, in which
clients now face serious concerns about the security and privacy of their data hosted in the …
clients now face serious concerns about the security and privacy of their data hosted in the …
Nature-inspired intrusion detection system for protecting software-defined networks controller
Abstract Software Defined Networks (SDN) is a new emerging networking architecture
facilitated by a separate controller. It has a centralized architecture that serves network …
facilitated by a separate controller. It has a centralized architecture that serves network …
A DDoS detection method based on feature engineering and machine learning in software-defined networks
Z Liu, Y Wang, F Feng, Y Liu, Z Li, Y Shan - Sensors, 2023 - mdpi.com
Distributed denial-of-service (DDoS) attacks pose a significant cybersecurity threat to
software-defined networks (SDNs). This paper proposes a feature-engineering-and machine …
software-defined networks (SDNs). This paper proposes a feature-engineering-and machine …