Sscl-ids: Enhancing generalization of intrusion detection with self-supervised contrastive learning
With the increasing diversity and complexity of cyber attacks on computer networks, there is
a growing demand for Intrusion Detection Systems (IDS) that can accurately categorize new …
a growing demand for Intrusion Detection Systems (IDS) that can accurately categorize new …
The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users
K Dietz, M Mühlhauser, J Kögel, S Schwinger… - IEEE …, 2024 - ieeexplore.ieee.org
Intrusion Detection Systems (IDS) tackle the challenging task of detecting network attacks as
fast as possible. As this is getting more complex in modern enterprise networks, Artificial …
fast as possible. As this is getting more complex in modern enterprise networks, Artificial …
Cml-ids: Enhancing intrusion detection in sdn through collaborative machine learning
The centralized control plane in Software-Defined Networking (SDN) offers significant
advancements in network management capabilities. However, SDN is also susceptible to …
advancements in network management capabilities. However, SDN is also susceptible to …
A data-driven solution for improving transferability of traffic flow feature selection
The expansion of Internet connectivity has increased cyber threats in computer networks.
Machine Learning (ML)-based Intrusion Detection Systems (IDS) have emerged as a …
Machine Learning (ML)-based Intrusion Detection Systems (IDS) have emerged as a …
[HTML][HTML] Enhancing trustworthiness in ML-based network intrusion detection with uncertainty quantification
A crucial role in the security of modern networks is played by Intrusion Detection Systems
(IDSs), security devices designed to identify and mitigate attacks to networks structure. Data …
(IDSs), security devices designed to identify and mitigate attacks to networks structure. Data …
Verifying the Robustness of Machine Learning based Intrusion Detection Against Adversarial Perturbation
Neural networks (NNs) have been extensively adapted to various security tasks, such as
spam detection, phishing, and intrusion detection. Particularly in IDS, NNs face significant …
spam detection, phishing, and intrusion detection. Particularly in IDS, NNs face significant …
[PDF][PDF] Dynamic network intrusion detection system in Software-Defined Networking
Software-Defined Networking (SDN) enhances network management by separating control
and data plane functionalities, but the centralized control plane increases the risk of cyber …
and data plane functionalities, but the centralized control plane increases the risk of cyber …
eMTD: Energy-Aware Moving Target Defense for Sustainable Solar-powered Sensor-based Smart Farms
Smart farms, as a way for better productivity and efficiency, have yet to be thoroughly studied
for their service quality amid cyber threats. This work introduces a proactive security …
for their service quality amid cyber threats. This work introduces a proactive security …
[PDF][PDF] The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users
J KÖGEL, S SCHWINGER, M SICHERMANN - 2024 - opus.bibliothek.uni-augsburg.de
ABSTRACT Intrusion Detection Systems (IDS) tackle the challenging task of detecting
network attacks as fast as possible. As this is getting more complex in modern enterprise …
network attacks as fast as possible. As this is getting more complex in modern enterprise …
[PDF][PDF] Machine Learning Models in Network Intrusion Detection Systems: Self-Supervised Detection of Malicious Flows and Traffic Patterns Recognition in …
P Golchin - d-nb.info
The recent increase in cyber-attacks highlights the critical need for reliable Network Intrusion
Detection Systems capable of detecting anomalies before they inflict substantial damage …
Detection Systems capable of detecting anomalies before they inflict substantial damage …