@inproceedings{GoertzFischerHackenberg, author = {G{\"o}rtz, Stefan and Fischer, Sebastian and Hackenberg, Rudolf}, title = {Generation of Distributed Denial of Service Network Data with Phyton and Scapy}, series = {CLOUD COMPUTING 2023 : The Fourteenth International Conference on Cloud Computing, GRIDs, and Virtualization, June 26 - 30, 2023, Nice, France}, booktitle = {CLOUD COMPUTING 2023 : The Fourteenth International Conference on Cloud Computing, GRIDs, and Virtualization, June 26 - 30, 2023, Nice, France}, publisher = {IARIA}, isbn = {978-1-68558-044-5}, pages = {8 -- 14}, abstract = {Distributed Denial of Service attacks are among the most common and widespread network attacks. Due to their nature, they are difficult to defend. Intrusion detection systems, based on machine learning, are a promising approach to counter this threat. But to train these systems, data sets with Distributed Denial of Service attacks are needed. An implemented Python program, which creates Denial of Services packets and simulates distributed sending by multithreading, is presented. Unlike synthetically generated data with the use of simulators, real network traffic is generated. This eliminates errors and offers a better basis of data, as machine learning algorithms need data that is as error-free as possible in order to learn efficiently.}, language = {en} }