A new method of hybrid time window embedding with transformer-based traffic data classification in IoT-networked environment

• Published in: Pattern analysis and applications : PAA Vol. 24; no. 4; pp. 1441 - 1449
• Main Authors: Kozik, Rafał, Pawlicki, Marek, Choraś, Michał
• Format: Journal Article
• Language: English
• Published: London Springer London 01.11.2021; Springer Nature B.V
• Subjects: Algorithms; Anomalies; Coders; Computer Science; Early warning systems; Embedding; Internet of Things; Machine learning; Neural networks; Original Article; Pattern Recognition; Traffic information; Transformers; Windows (intervals); Deep learning; Transformers; Anomaly detection

The Internet of Things (IoT) appliances often expose sensitive data, either directly or indirectly. They may, for instance, tell whether you are at home right now or what your long or short-term habits are. Therefore, it is crucial to protect such devices against adversaries and has in place an earl...