Kommunikationsnetze / Multimedia Kommunikation
Pegah Golchin received her M.Sc. degree in Telecommunication Network Engineering from Isfahan University of Technology in 2018. Since 2019 she worked as a computer science research assistant at HHU and she joined the multimedia communication lab as a Ph.D. student in 2021. In her research, she mainly focuses on solving SDN cyber security problems leveraging AI methods.
Applying Machine Learning and Deep Learning approaches in
I am looking for motivated students who would like to start with their bachelor's or master's theses. Feel free to contact me if you are interested in applying AI to solve the network security problems.
Apart from that, you can also find a list of open topics here.
Year | Type | Student | Title | Co-supervisors and notes | Status |
---|---|---|---|---|---|
2023 | Master | Kexin Wang |
Generating adversarial C2 Communication Attacks Leveraging the Shift Distribution Strategy and Online Learning feedback |
In progress |
|
2023 | Master | Chengbo Zhou | A Collaborative Machine Learning-based Network Intrusion Detection Architecture in Software Defined Networking | Pratyush Agnihotri |
Completed Awarded for the Best Master Thesis at KOM (2023) |
2023 | Master | Yizi Liu | In-Network Intrusion Detection System Leveraging Decision Tree Model Inference | Fridolin Siegmund | Completed |
2022 | Bachelor | Leonard Anderweit | In-Network DDoS Attack Detection Leveraging Time Series Data in Programmable Data Planes | Ralf Kundel | Completed |
2021 | Master | Stefan Stegmueller | Generative Adversarial Network-based Robustness Evaluation of Machine Learning Classification Algorithms for DDoS-Attacks | External thesis (DE-CIX), Ralf Kundel |
Completed Awarded for the Best Master Thesis at KOM (2022) |
Year | Type | Title | Co-supervisors and notes |
---|---|---|---|
SoSe23 | MMCS | Generating Perturbed Network Intrusion Features | - |
WiSe22 | MMCS | Machine Learning-based Intrusion Detection Systems in Software-Defined Networking | - |
SoSe22 | MMCS | Robustness Evaluation of ML-based NIDS Using Generative Adversarial Networks | - |
SoSe22 | KOM Lab | Network Monitoring in SDN | Pratyush Agnihotri |
WiSe 21 | MMCS | Encrypted Traffic Classification Leveraging Machine Learning and Deep Learning Models | - |
WiSe 21 | KOM Lab | Telcaria Alviu: Network Traffic Monitoring and Profiling | Pegah Golchin |