A Survey on Explainable Artificial Intelligence for Internet Traffic Classification and Prediction, and Intrusion Detection
With the increasing complexity and scale of modern networks, the demand for transparent
and interpretable Artificial Intelligence (AI) models has surged. This survey comprehensively …
and interpretable Artificial Intelligence (AI) models has surged. This survey comprehensively …
When adversarial perturbations meet concept drift: an exploratory analysis on ml-nids
We scrutinize the effects of" blind''adversarial perturbations against machine learning (ML)-
based network intrusion detection systems (NIDS) affected by concept drift. There may be …
based network intrusion detection systems (NIDS) affected by concept drift. There may be …
Evaluating The Explainability of State-of-the-Art Machine Learning-based Online Network Intrusion Detection Systems
A Kumar, VLL Thing - arxiv preprint arxiv:2408.14040, 2024 - arxiv.org
Network Intrusion Detection Systems (NIDSs) which use machine learning (ML) models
achieve high detection performance and accuracy while avoiding dependence on fixed …
achieve high detection performance and accuracy while avoiding dependence on fixed …
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 …
An Empirical Study on Learning Models and Data Augmentation for IoT Anomaly Detection
Among many other security applications, anomaly detection is one of the biggest users of
deep learning methods. This growing popularity is mainly driven by two common beliefs:(i) …
deep learning methods. This growing popularity is mainly driven by two common beliefs:(i) …
ExpIDS: A Drift-Adaptable Network Intrusion Detection System with Improved Explainability
A Kumar, KW Fok, VLL Thing - 2024 34th International …, 2024 - ieeexplore.ieee.org
Despite all the advantages associated with Network Intrusion Detection Systems (NIDSs)
that utilize machine learning (ML) models, there is a significant reluctance among cyber …
that utilize machine learning (ML) models, there is a significant reluctance among cyber …
[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 …