Mar 15, 2021 · We propose an anomaly detection method based on cosine similarity for in-vehicle network through the analysis of self-similarity of the CAN bus.
Mar 15, 2021 · We propose an anomaly detection method based on cosine similarity for in-vehicle network through the analysis of self-similarity of the CAN bus.
Finally, we also showed that the cosine similarity in the CAN bus is a meaningful feature to identify and classify the types of attacks on target CAN IDs.
The cosine similarity value gives clear boundary for detecting an abnormality. • The abnormality could be identified with high accuracy and fast detection speed ...
People also ask
What is cosine similarity method?
What is cosine similarity language model?
This paper reviews the research on anomaly detection for in-vehicle networks, more specifically for the CAN bus.
This paper presents a new method called AMF-LSTM for abnormal traffic detection by using deep learning model. We use the statistical features of multi-flows ...
Cosine similarity based anomaly detection methodology for the CAN bus. BI Kwak, ML Han, HK Kim. Expert Systems with Applications 166, 114066, 2021. 41, 2021.
In this paper, we propose a novel system that uses a deep neural network (DNN) to detect anomalous CAN bus messages.
Missing: Cosine | Show results with:Cosine
A method to detect and identify abnormalities in vehicular networks based on the periodic event-triggered interval of the controller area network (CAN) ...
Apr 27, 2022 · This paper uses graph pattern matching for the first time to detect the CAN bus's anomaly and defines the graph distance for graph pattern ...