Sok: Explainable machine learning for computer security applications
Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
Bad design smells in benchmark nids datasets
Synthetically generated benchmark datasets are vitally important for machine learning and
network intrusion research. When producing intrusion datasets for research, providers make …
network intrusion research. When producing intrusion datasets for research, providers make …
E-XAI: Evaluating Black-Box Explainable AI Frameworks for Network Intrusion Detection
The exponential growth of intrusions on networked systems inspires new research directions
on develo** artificial intelligence (AI) techniques for intrusion detection systems (IDS). In …
on develo** artificial intelligence (AI) techniques for intrusion detection systems (IDS). In …
SoK: Pragmatic assessment of machine learning for network intrusion detection
Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For
Network Intrusion Detection (NID), however, scientific advances in ML are still seen with …
Network Intrusion Detection (NID), however, scientific advances in ML are still seen with …
XAI-IDS: Toward Proposing an Explainable Artificial Intelligence Framework for Enhancing Network Intrusion Detection Systems
The exponential growth of network intrusions necessitates the development of advanced
artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the …
artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the …
Causal effect analysis-based intrusion detection system for IoT applications
Intrusion detection systems (IDSs) are employed at various levels in the network to either
detect or prevent an intrusion that could cause irrecoverable data damage in IoT …
detect or prevent an intrusion that could cause irrecoverable data damage in IoT …
XAI-based Feature Selection for Improved Network Intrusion Detection Systems
Explainability and evaluation of AI models are crucial parts of the security of modern
intrusion detection systems (IDS) in the network security field, yet they are lacking …
intrusion detection systems (IDS) in the network security field, yet they are lacking …
Discovering non-metadata contaminant features in intrusion detection datasets
Most newly proposed detection methods in intrusion detection incorporate machine learning
models to distinguish between benign and malicious traffic. The models are validated on a …
models to distinguish between benign and malicious traffic. The models are validated on a …
Let us Unveil Network Intrusion Features: Enhancing Network Intrusion Detection Systems via XAI-based Feature Selection
O Arreche, T Guntur, M Abdallah - 2024 - researchsquare.com
Explainability and evaluation of AI models are crucial parts of the security of modern
intrusion detection systems (IDS) in the network security field, yet they are lacking …
intrusion detection systems (IDS) in the network security field, yet they are lacking …
Detection of DoS and DDoS attacks on 5G network slices using deep learning approach
MS Khan - 2023 - search.proquest.com
A new degree of connectedness and interaction has been introduced by the developmentof
5G networks. By dividing a physical network into several logical networks, 5G network …
5G networks. By dividing a physical network into several logical networks, 5G network …