Anomaly Detection System for Altered Signal Values within the Intra-Vehicle NetworkIn-vehicle networkvehicle cybersecurityanomaly detectionintrusion detectionA modern vehicle is a complex system of sensors, act
Among them, attack detection is one of more concerned technologies and has become increasing critical to in-vehicle network security. The intrusion detection system (IDS) is a significant tool in securing networks and information systems over the past decades [8]. The remainder of the paper is ...
For industrial big data, anomaly detection for multivariate time series data is of critical strategic significance. However, the complexity of industrial e
anomaly detection in the last decade. We then present a systematic categorization of methodologies for anomaly detection. As the notion of anomaly depends on context, we identify different objects-of-interest and publicly available datasets in anomaly detection. Since anomaly detection is a time-...
Following this consideration, Generative Adversarial Networks (GANs) have gained more attention in anomaly detection research due to their outstanding performance in constructing images, affording data augmentation, and dealing with implicit data in complex scenarios [8]. GANs consist of two competing ...
An approach for detecting anomalous flows in a network using header field entropy. This can be useful in detecting anomalous or malicious traffic that may attempt to “hide” or inject itself into legitimate flows. A malicious endpoint might attempt to send a control message in underutilized heade...
The overall functionality of the security controller, illustrated in Fig. 1, comprises two major processes. First, a device-level analysis is applied to identify intra and internet traffic anomalies. Machine learning-based anomaly detection refers to the identification of MUD profiles of the devices ...
It is often difficult to understand the complex dynamics of events in real-time scenarios due to camera movements, cluttered backgrounds, and occlusion. Existing anomaly detection systems are not efficient because of high intra-class variations and inter-class similarities existing among activities. ...
generative adversarial networks; video anomaly detection; reconstruction1. Introduction The proliferation of surveillance videos has driven the advances in video anomaly detection, which focuses on mining unusual patterns from these videos. In video anomaly detection, anomalies refer to events or behaviors ...
generative adversarial networks; video anomaly detection; reconstruction1. Introduction The proliferation of surveillance videos has driven the advances in video anomaly detection, which focuses on mining unusual patterns from these videos. In video anomaly detection, anomalies refer to events or behaviors ...