Electronics MDPI’s Post

🎉 Excited to share that our work, based on my master’s thesis, has been published in the prestigious Electronics MDPI journal as part of the Special Issue Applications of Deep Learning in Cyber Threat Detection ! 🚀 Titled "Unsupervised Anomaly Detection and Explanation in Network Traffic with Transformers," this work presents our research on a Transformer Autoencoder-based (TAE) approach for unsupervised cyber-attack detection and perturbation-based explanation procedure that leverages attention weights to deliver detailed insights into predictions across multiple dimensions of network traffic data. This publication marks an important step toward advancing state-of-the-art approaches in network intrusion detection systems. I would like to express my gratitude to Fraunhofer IOSB-AST, Technische Universität Ilmenau , and my supervisors, Dr.-Ing. Andre Kummerow and Dr. Markus Eisenbach. 📖 Read more about our work here: website:https://lnkd.in/e8vp38qC PDF:https://lnkd.in/eAHdCsYh #CyberSecurity #DeepLearning #AnomalyDetection #Transformers #Research #MDPI #Fraunhofer #TechnicalUniversityIlmenau