Short Bio

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.

Research Interests

Applying Machine Learning and Deep Learning approaches in

SDN monitoring (traffic classification)
Network Intrusion Detection Systems (Network security)
SDN data plane (in P4 switches)

Projects

AI-NET PROTECT
Software Campus

Open Thesis

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.

Supervised Thesis

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)*

Supervised Labs and Seminars

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

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