Kolloquiumsvortrag 18. November 2025, Tibet Erten (Betreuer: Al Sardy/Muhammad)
A Transformer-Based Approach to Intrusion Detection in IoT Networks
The Internet of Things (IoT) is transforming industries like healthcare and industrial automation, while becoming a key part of everyday life through smart home devices. However, the complex and interconnected nature of IoT ecosystems creates significant cybersecurity challenges. These are worsened by the large number of devices, diverse communication protocols, and limited security features in many IoT devices, making them vulnerable to various cyberattacks. This thesis explores a Transformer-based intrusion detection system (IDS) to address these issues, aiming to detect and mitigate attacks using AI-driven anomaly detection techniques.
Uhrzeit: 10:15 Uhr
Ort: Raum 04.137, Martensstr. 3, Erlangen
oder
Zoom-Meeting beitreten:
https://fau.zoom-x.de/j/68350702053?pwd=UkF3aXY0QUdjeSsyR0tyRWtLQ0hYUT09
Meeting-ID: 683 5070 2053
Kenncode: 647333