Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic. - Christoph Hardegen; Benedikt Pfülb; Sebastian Rieger; Alexander Gepperth; Sven Reißmann (CNSM, 2019)

A Study of Deep Learning for Network Traffic Data Forecasting. - Benedikt Pfülb; Christoph Hardegen; Alexander Gepperth; Sebastian Rieger (ICANN (4), 2019)

Prediction-based Flow Routing in Programmable Networks with P4. - Christoph Hardegen; Sebastian Rieger (CNSM, 2020)

Predicting Network Flow Characteristics Using Deep Learning and Real-World Network Traffic. - Christoph Hardegen; Benedikt Pfülb; Sebastian Rieger; Alexander Gepperth (IEEE Trans. Netw. Serv. Manag., 2020)

A Hierarchical Architecture and Probabilistic Strategy for Collaborative Intrusion Detection. - Christoph Hardegen; Mike Petersen; Chukwuebuka Ezelu; Timo Geier; Sebastian Rieger; Ulrich Buehler (CNS, 2021)

Scope-based Flow Monitoring to Improve Traffic Analysis in Programmable Networks. - Christoph Hardegen (CNSM, 2022)

Intent-Driven Path State Monitoring to Enable Centralized State-Aware Flow Steering. - Christoph Hardegen (CNSM, 2022)

Multi-step Attack Detection and Mitigation Enhancing In-Network Flow Classification. - Christoph Hardegen; Sebastian Rieger; Timo Geier (CommNet, 2022)

Generative Pattern Dissemination for Collaborative Intrusion Detection. - Mike Petersen; Christoph Hardegen; Ulrich Buehler (CIoT, 2023)

Predictive Flow Load Profiling for Intelligent Network Routing Decisions. - Christoph Hardegen (NoF, 2023)