scholar.google.com › citations
Abstract: We present a method for attack detection in public transport networks. Through unsupervised machine learning, the daily data of the transportation ...
We present a method for attack detection in public transport networks. Through unsupervised machine learning, the daily data of the transportation system is ...
Any network link attack in the source network will affect the security of the industrial control system, resulting in economic loss of the industrial control ...
This thesis designs an anomaly attack detection based on self-organizing mapping algorithm to improve the accuracy of anomaly detection technology. Through the ...
Inproceedings,. Data-Driven Attack Anomaly Detection in Public Transport Networks. Y. Rui, N. Wong, H. Guo, and W. Goh. APWCS, page 1-5. IEEE, (2019 ). 1. 1 ...
Our paper proposes a data analytics-driven network anomaly detection model, which is uniquely complemented with a visualization layer.
We propose an analytical framework that leverages real-time road link sensory data to conduct online data-driven transportation network anomaly detection.
[PDF] Local Anomaly Detection in Smart Public Transport Vehicles
www.akesson.nl › liauw-a-fong-thesis
This thesis delves into the realm of anomaly detection within smart public transport vehicles. A domain marked by the integration of complex, ...
Missing: Attack | Show results with:Attack
Apr 12, 2024 · In this paper, the NSL-KDD data set is analyzed and used to study the effectiveness of various classification algorithms in detecting anomalies ...
We propose a multi-tiered anomaly detection framework which utilizes spare processing capabilities of the distributed RSU network in combination with the cloud.