Anomaly and intrusion detection using deep learning for software-defined networks: A survey
Abstract Software-Defined Networks (SDN) represent an adaptable paradigm for dealing
with network users' dynamic demands. Confidentiality, integrity, and availability are …
with network users' dynamic demands. Confidentiality, integrity, and availability are …
HDLNIDS: hybrid deep-learning-based network intrusion detection system
Attacks on networks are currently the most pressing issue confronting modern society.
Network risks affect all networks, from small to large. An intrusion detection system must be …
Network risks affect all networks, from small to large. An intrusion detection system must be …
An efficient optimal security system for intrusion detection in cloud computing environment using hybrid deep learning technique
Users have been urged to embrace a cloud-based environment by recent technologies and
advancements. Because of the dispersed nature of cloud solutions, security is a major …
advancements. Because of the dispersed nature of cloud solutions, security is a major …
Securing mobile edge computing using hybrid deep learning method
In recent years, Mobile Edge Computing (MEC) has revolutionized the landscape of the
telecommunication industry by offering low-latency, high-bandwidth, and real-time …
telecommunication industry by offering low-latency, high-bandwidth, and real-time …
Building a cloud-IDS by hybrid bio-inspired feature selection algorithms along with random forest model
The adoption of cloud computing has become increasingly widespread across various
domains. However, the inherent security vulnerabilities of cloud computing pose significant …
domains. However, the inherent security vulnerabilities of cloud computing pose significant …
[HTML][HTML] Early Intrusion Detection System using honeypot for industrial control networks
Abstract Man-in-the-Middle (MITM) and Distributed Denial of Service (DDoS) attacks are
significant threats, especially to Industrial Control Systems (ICS). The honeypot is one of the …
significant threats, especially to Industrial Control Systems (ICS). The honeypot is one of the …
[HTML][HTML] DeepDetect: An innovative hybrid deep learning framework for anomaly detection in IoT networks
The presence of threats and anomalies in the Internet of Things infrastructure is a rising
concern. Attacks, such as Denial of Service, User to Root, Probing, and Malicious operations …
concern. Attacks, such as Denial of Service, User to Root, Probing, and Malicious operations …
A soft actor-critic reinforcement learning algorithm for network intrusion detection
Network intrusion detection plays a very important role in network security. Although current
deep learning-based intrusion detection algorithms have achieved good detection …
deep learning-based intrusion detection algorithms have achieved good detection …
F-NIDS—A Network Intrusion Detection System based on federated learning
The rise of IoT networks has presented fresh challenges in terms of scalability and security
for distributed Network Intrusion Detection Systems (NIDS) due to privacy concerns. While …
for distributed Network Intrusion Detection Systems (NIDS) due to privacy concerns. While …
[HTML][HTML] A sequential deep learning framework for a robust and resilient network intrusion detection system
Ensuring the security and integrity of computer and network systems is of utmost importance
in today's digital landscape. Network intrusion detection systems (NIDS) play a critical role in …
in today's digital landscape. Network intrusion detection systems (NIDS) play a critical role in …